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Advances on machine learning of graphs, covering the reading list of recent top academic conferences.

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Graph Learning Reading List

I scanned over the accepted paper lists of top machine learning and data mining conferences for interests in graph learning. We also add a snippset tutorial Parse Website to teach you how to obtain the titles and authors from the official conference website.

We also create the reading lists for 2022 and 2023 for convenience.

  1. Attribute-missing Graph Clustering Network

    Tu, Wenxuan*; Guan, Renxiang; Zhou, Sihang; Ma, Chuan; Peng, Xin; Cai, Zhiping; Liu, Zhe; Cheng, Jieren; Liu, Xinwang

  2. Cell Graph Transformer for Nuclei Classification

    Lou, Wei; Li, Guanbin; Wan, Xiang; Li, Haofeng*

  3. Panoptic Scene Graph Generation with Semantics-prototype Learning

    Li, Li*; Ji, Wei; Wu, Yiming; Li, Mengze; QIN, YOU; Wei, Lina; Zimmermann, Roger

  4. A Transfer Approach Using Graph Neural Networks in Deep Reinforcement Learning

    Yang, Tianpei*; You, Heng; Hao, Jianye; Zheng, Yan; Taylor, Matthew E.

  5. SGFormer: Semantic Graph Transformer for Point Cloud-based 3D Scene Graph Generation

    Lv, Changsheng; Qi, Mengshi*; Li, Xia; Yang, Zhengyuan; Ma, Huadong

  6. Multi-Prototype Space Learning for Commonsense-based Scene Graph Generation

    Chen, Lianggangxu; Song, Youqi; Cai, Yiqing ; Lu, Jiale; Li, Yang; Xie, Yuan; Wang, Changbo; He, Gaoqi*

  7. Dynamic Sub-graph Distillation for Robust Semi- supervised Continual Learning

    Fan, Yan*; Wang, Yu; Zhu, Pengfei; Hu, Qinghua

  8. Multimodal Event Causality Reasoning with Scene Graph Enhanced Interaction Network

    Liu, Jintao*; wei, kaiwen; Liu, Chenglong

  9. MDGNN: Multi-relational Dynamic Graph Neural Network for Comprehensive and Dynamic Stock Investment Prediction

    Qian, Hao*; Zhou, Hongting; Zhao, Qian; Chen, Hao; Yao, Hongxiang; Wang, Jingwei; Liu, Ziqi; Yu, Fei; Zhang, Zhiqiang; Zhou, Jun

  10. TextGT: A Double-View Graph Transformer on Text for Aspect-Based Sentiment Analysis

    Yin, Shuo*; Zhong, Guoqiang

  11. Identifiability of Direct Effects from Summary Causal Graphs

    Ferreira, Simon M*; Assaad, Charles K.

  12. Gramformer: Learning Crowd Counting via Graph-Modulated Transformer

    LIN, Hui; Ma, Zhiheng; Hong, Xiaopeng*; shangguan, qinnan; Meng, Deyu

  13. Hawkes-enhanced Spatial-Temporal Hypergraph Contrastive Learning based on Criminal Correlations

    Liang, Ke*; Zhou, Sihang; Liu, Meng; Liu, Yue; Tu, Wenxuan; Zhang, Yi; Fang, Liming; Liu, Zhe; Liu, Xinwang

  14. Rethinking Causal Relationships Learning in Graph Neural Networks

    Gao, Hang; chengyu, yao; Li, Jiangmeng; Si , Lingyu; Jin, Yifan; Wu, Fengge*; Zheng, Changwen; Liu, Huaping

  15. Propagation Tree is not Deep: Adaptive Graph Contrastive Learning Approach for Rumor Detection

    Cui, Chaoqun*; Jia, Caiyan

  16. Label Attentive Distillation for GNN-based Graph Classification

    Hong, Xiaobin*; Li, Wenzhong; Wang, Chaoqun; Lin, Mingkai; Lu, Sanglu

  17. A Non-parametric Graph Clustering Framework for Multi-view Data

    yu, shengju*; Wang, Siwei; Dong, Zhibin; Tu, Wenxuan; Liu, Suyuan; Lv, Zhao; Li, Pan; Wang, Miao; Zhu, En

  18. An Efficient Subgraph-inferring Framework for Large-scale Heterogeneous Graphs

    Zhou, Wei; Huang, Hong*; Shi, Ruize; Yin, Kehan khyin; Jin, Hai

  19. TREE-G: Decision Trees Contesting Graph Neural Networks

    Bechler-Speicher, Maya*; Globerson, Amir; Gilad- Bachrach, Ran

  20. TD$^2$-Net: Toward Denoising and Debiasing for Video Scene Graph Generation

    Lin, Xin*; Shi, Chong; Zhan, Yibing; Yang, Zuopeng; Wu, Yaqi; Tao, Dacheng

  21. ADA-GAD: Anomaly-Denoised Autoencoders for Graph Anomaly Detection

    He, Junwei*; Xu, Qianqian; Jiang, Yangbangyan; Wang, Zitai; Huang, Qingming

  22. Reverse Multi-Choice Dialogue Commonsense Inference with Graph-of-Thought

    Zheng, Li*; Fei, Hao; Li, Fei; Li, Bobo; Liao, Lizi; Ji, Donghong; Teng, Chong

  23. MINES: Message Intercommunication for Inductive Relation Reasoning over Neighbor- Enhanced Subgraphs

    Liang, Ke*; Meng, Lingyuan; Zhou, Sihang; Tu, Wenxuan; Wang, Siwei; Liu, Yue; Liu, Meng; Zhao, Long; Dong, Xiangjun; Liu, Xinwang

  24. HGE: Embedding Temporal Knowledge Graphs in a Product Space of Heterogeneous Geometric Subspaces

    Pan, Jiaxin*; Nayyeri, Mojtaba; Li, Yinan; Staab, Steffen

  25. Learning to Approximate Adaptive Kernel Convolution on Graphs

    Sim, Jaeyoon*; Jeon, Sooyeon; Choi, InJun; Wu, Guorong; Kim, Won Hwa

  26. Graph Context Transformation Learning for Progressive Correspondence Pruning

    Guo, Junwen; Xiao, Guobao*; Wang, Shiping; Yu, Jun

  27. Towards Inductive Robustness: Distilling and Fostering Wave-induced Resonance in Transductive GCNs Against Graph Adversarial Attacks

    Liu, Ao*; Li, Wenshan; Li, Tao; Li, Beibei; Huang, Hanyuan; Zhou, Pan

  28. Parameterization of (Partial) Maximum Satisfiability Above Matching in a Variable- Clause Graph

    Alferov, Vasily; Bliznets, Ivan*; Brilliantov, Kirill

  29. Multi-Scene Generalized Trajectory Global Graph Solver with Composite Nodes for Multiple Object Tracking

    Gao, Yan; Xu, Haojun; Li, Jie; Wang, Nannan; Gao, Xinbo*

  30. SEA-GWNN: Simple and Effective Adaptive Graph Wavelet Neural Network

    Deb, Swakshar*; Rahman, Sejuti; Rahman, Shafin

  31. A Cross-View Hierarchical Graph Learning Hypernetwork for Skill Demand-Supply Joint Prediction

    Chao, Wen Shuo*; Qiu, Zhaopeng; Wu, Likang; Guo, Zhuoning; Zheng, Zhi; Zhu, Hengshu; Liu, Hao

  32. Exploring Large Language Model for Graph Data Understanding in Online Job Recommendations

    Wu, Likang*; Qiu, Zhaopeng; Zheng, Zhi; Zhu, Hengshu; Chen, Enhong

  33. MGNet: Learning Correspondences via Multiple Graphs

    LUANYUAN, DAI; Du, Xiaoyu; Zhang, Hanwang; Tang, Jinhui*

  34. X-RefSeg3D: Enhancing Referring 3D Instance Segmentation via Structured Cross-Modal Graph Neural Networks

    Qian, Zhipeng*; Ma, Yiwei; Ji, Jiayi; Sun, Xiaoshuai

  35. WaveNet: Tackling Non-Stationary Graph Signals via Graph Spectral Wavelets

    Yang, Zhirui*; hu, yulan; Ouyang, Sheng; Liu, Jingyu; Wang, Shuqiang; Ma, Xibo; Wang, Wenhan; Su, Hanjing; Liu, Yong

  36. Kumaraswamy Wavelet for Heterophilic Scene Graph Generation

    Chen, Lianggangxu; Song, Youqi; Lin, Shaohui; Wang, Changbo; He, Gaoqi*

  37. Feature Transportation Improves Graph Neural Networks

    Eliasof, Moshe*; Haber, Eldad; Treister, Eran

  38. Learning to Optimize Permutation Flow Shop Scheduling via Graph-based Imitation Learning

    Li, Longkang; Liang, Siyuan; Zhu, Zihao; Ding, Chris H.Q.; Zha, Hongyuan; Wu, Baoyuan*

  39. Improving Distinguishability of Class for Graph Neural Networks

    He, Dongxiao; Liu, Shuwei; Yu, Zhizhi*; Xu, Guangquan; Ge, Meng; Feng, Zhiyong

  40. Dynamic Reactive Spiking Graph Neural Network

    Zhao, Han; Yang, Xu; Deng, Cheng*; Yan, Junchi

  41. G^2SAM: Graph-Based Global Semantic Awareness Method for Multimodal Sarcasm Detection

    wei, yiwei*; Yuan, Shaozu; zhou, hengyang; Wang, Longbiao; Yan, Zhiling; Yang, Ruosong; Chen, Meng

  42. Protein 3D Graph Structure Learning for Robust Structure-based Protein Property Prediction

    Huang, Yufei*; Li, Siyuan; Wu, Lirong; Su, Jin; Lin, Haitao; Zhang, Odin; Liu, Zihan; Gao, Zhangyang; Zheng, Jiangbin; Li, Stan Z.

  43. Every Node is Different: Dynamically Fusing Self- Supervised Tasks for Attributed Graph Clustering

    Zhu, Pengfei; Wang, Qian; Wang, Yu*; Li, Jialu; Hu, Qinghua

  44. Graph Reasoning Transformers for Knowledge- Aware Question Answering

    Zhao, Ruilin; Zhao, Feng*; Hu, Liang; Xu, Guandong

  45. Towards Continual Knowledge Graph Embedding via Incremental Distillation

    Liu, Jiajun; Wenjun, Ke*; Wang, Peng; Shang, Ziyu; Jinhua, Gao; Li, Guozheng; Ji, Ke; Liu, Yanhe

  46. Patch-wise Graph Contrastive Learning for Image Translation

    Jung, Chanyong*; Kwon, Gihyun; Ye, Jong Chul

  47. CI-STHPAN: Pre-Trained Attention Network for Stock Selection with Channel-Independent Spatio-Temporal Hypergraph

    Xia, Hongjie; Ao, Huijie; Li, Long; Liu, Yu; Liu, Sen; Ye, Guangnan*; Chai, Hongfeng

  48. Linear-Time Algorithms for Front-Door Adjustment in Causal Graphs

    Wienöbst, Marcel*; van der Zander, Benito; Liskiewicz, Maciej

  49. Rethinking Dimensional Rationale in Graph Contrastive Learning from Causal Perspective

    Ji, Qirui; Li, Jiangmeng*; Hu, Jie; Wang, Rui; Zheng, Changwen; Xu, Fanjiang

  50. Homophily-Related: Adaptive Hybrid Graph Filter for Multi-View Graph Clustering

    Wen, Zichen*; Ling, Yawen; Ren, Yazhou; Wu, TianYi; Chen, Jianpeng; Pu, Xiaorong; Hao, Zhifeng; He, Lifang

  51. Adaptive Feature Imputation with Latent Graph for Deep Incomplete Multi-view Clustering

    Pu, Jingyu*; Cui, Chenhang; Chen, Xinyue; Ren, Yazhou; Pu, Xiaorong; Hao, Zhifeng; Yu, Philip S; He, Lifang

  52. Robust Node Classification on Graph Data with Graph and Label Noise

    Zhu, Yonghua*; Feng, Lei; Deng, Zhenyun; Chen, Yang; Amor, Robert; Witbrock, Michael J

  53. A New Mechanism for Eliminating Implicit Conflict in Graph Contrastive Learning

    He, Dongxiao; Zhao, Jitao; Huo, Cuiying; Yongqi, Huang; Huang, Yuxiao*; Feng, Zhiyong

  54. COMBHelper: A Neural Approach to Reduce Search Space for Graph Combinatorial Problems

    Tian, Hao*; Medya, Sourav; Ye, Wei

  55. Deep Contrastive Graph Learning with Clustering-Oriented Guidance

    Chen, Mulin*; Wang, Bocheng; Li, Xuelong

  56. Enhancing Multi-scale Diffusion Prediction via Sequential Hypergraphs and Adversarial Learning

    Jiao, Pengfei*; Chen, Hongqian; Bao, Qing; Zhang, Wang; Wu, Huaming

  57. Rethinking Graph Masked Autoencoders through Alignment and Uniformity

    Wang, Liang*; Tao, Xiang; Liu, Qiang; Wu, Shu; Wang, Liang

  58. Knowledge Graph Prompting for Multi- Document Question Answering

    Wang, Yu*; Lipka, Nedim; Rossi, Ryan A.; Siu, Alexa; Zhang, Ruiyi; Derr, Tyler

  59. Dual-channel Learning Framework for Drug-Drug Interaction Prediction via Relation-aware Heterogeneous Graph Transformer

    Su, Xiaorui; Hu, Pengwei; You, Zhu-Hong; Yu, Philip S; Hu, Lun*

  60. NodeMixup: Tackling Under-Reaching for Graph Neural Networks

    Lu, Weigang*; Guan, Ziyu; Zhao, Wei; Yang, Yaming; jin, long

  61. Neural Gaussian Similarity Modeling for Differential Graph Structure Learning

    Fan, Xiaolong*; Gong, Maoguo; Wu, Yue; Tang, Zedont; Liu, Jieyi

  62. Sterling: Synergistic Representation Learning on Bipartite Graphs

    Jing, Baoyu*; Yan, Yuchen; Ding, Kaize; Park, Chanyoung; Zhu, Yada; Liu, Huan; Tong, Hanghang

  63. Factorized Explainer for Graph Neural Networks

    Huang, Rundong; Shirani, Farhad; Luo, Dongsheng*

  64. Hyperbolic Graph Diffusion Model

    Wen, Lingfeng; TANG, XUAN; Ouyang, Mingjie; Shen, Xiangxiang; Yang, Jian; Zhu, Daxin; Chen, Mingsong; Wei, Xian*

  65. Union Subgraph Neural Networks

    Xu, Jiaxing*; Zhang, Aihu; Bian, Qingtian; Dwivedi, Vijay Prakash; Ke, Yiping

  66. GOODAT: Towards Test-time Graph Out-of- Distribution Detection

    Wang, Luzhi*; Jin, Di; Zhang, He; Liu, Yixin; He, Dongxiao; Wang, Wenjie; Pan, Shirui; Chua, Tat- Seng

  67. DHGCN: Dynamic Hop Graph Convolution Network for Self-supervised Point Cloud Learning

    Jiang, Jincen; Zhao, Lizhi; Lu, Xuequan; Hu, Wei; Razzak, Imran; wang, meili*

  68. HONGAT: Graph Attention Networks in the Presence of High-Order Neighbors

    Zhang, Heng-Kai*; Zhang, Yi-Ge; Zhou, Zhi; Li, Yu- Feng

  69. Temporal Graph Contrastive Learning for Sequential Recommendation

    Zhang, Shengzhe*; Chen, Liyi; Wang, Chao; Li, Shuangli; Xiong, Hui

  70. End-to-End Verification for Subgraph Solving

    Gocht, Stephan ; McCreesh, Ciaran*; Myreen, Magnus; Nordström, Jakob; Oertel, Andy; Tan, Yong Kiam

  71. An Autoregressive Text-to-Graph Framework for Joint Entity and Relation Extraction

    Zaratiana, Urchade*; Tomeh, Nadi; Holat, Pierre; Charnois, Thierry

  72. Beyond Atomic Facts: Modeling Relationships between Facts for Knowledge Graph Reasoning

    Xiong, Bo*; Nayyeri, Mojtaba; Luo, Linhao; Wang, Zihao; Pan, Shirui; Staab, Steffen

  73. Open-Set Graph Domain Adaptation via Separate Domain Alignment

    Wang, Yu; Zhu, Ronghang*; Ji, Pengsheng; Li, Sheng

  74. Motif-aware Riemannian Graph Neural Network with Generative-Contrastive Learning

    Sun, Li*; Huang, Zhenhao; Wang, Zixi; Wang, Feiyang; Peng, Hao; Yu, Philip S

  75. A Variational Autoencoder for Neural Temporal Point Processes with Dynamic Latent Graphs

    Yang, Sikun*; Zha, Hongyuan

  76. SURER: Structure-Adaptive Unified Graph Neural Network for Multi-view Clustering

    Wang, Jing; Feng, Songhe*; Lyu, Gengyu; Yuan, Jiazheng

  77. TEILP: Time prediction over knowledge graphs via logical reasoning

    Xiong, Siheng*; Yang, Yuan; Payani, Ali; Kerce, James C; Fekri, Faramarz

  78. Structure-CLIP: Towards Scene Graph Knowledge to Enhance Multi-modal Structured Representations

    Huang, Yufeng*; Tang, Jiji; Chen, Zhuo; Zhang, Rongsheng; Zhang, Xinfeng; Chen, Weijie; Zhao, Zeng; Zhao, Zhou; Lv, Tangjie; Hu, Zhipeng; Zhang, Wen

  79. Conformal Crystal Graph Transformer with Robust Encoding of Periodic Invariance

    Wang, Yingheng*; Kong, Shufeng; Gregoire, John; Gomes, Carla P

  80. Bidirectional Temporal Plan Graph: Enabling Switchable Passing Orders for More Efficient Multi-Agent Path Finding Plan Execution

    Su, Yifan*; Veerapaneni, Rishi; Li, Jiaoyang

  81. Refining Latent Homophilic Structures over Heterophilic Graphs for Robust Graph Convolution Networks

    Qiu, Chenyang*; Nan, Guoshun; Xiong, Tianyu; Deng, Wendi; Wang, Di; Teng, Zhiyang; Sun, Lijuan; Cui, Qimei; Tao, Xiaofeng

  82. Improving Expressive Power of Spectral Graph Neural Networks with Eigenvalue Correction

    Lu, Kangkang; yu, yanhua*; Fei, Hao; Li, Xuan; Yang, Zixuan; Guo, Zirui; Liang, Meiyu; Yin, Mengran; Chua, Tat-Seng

  83. Graph Contextual Contrasting for Multivariate Time Series Classification

    Wang, Yucheng*; Xu, Yuecong; Yang, Jianfei; Wu, Min; Li, Xiaoli; Xie, Lihua; Chen, Zhenghua

  84. ECHO-GL: Earnings Calls-driven Heterogeneous Graph Learning for Stock Movement Prediction

    Liu, Mengpu*; Zhu, Mengying; Wang, Xiuyuan; Ma, Guofang; Yin, Jianwei; Zheng, Xiaolin

  85. Deep Semantic Graph Transformer for Multi- view 3D Human Pose Estimation

    Zhang, Lijun*; zhou, kangkang; Lu, Feng; Zhou, Xiang-Dong; Shi, Yu

  86. FairSIN: Achieving Fairness in Graph Neural Networks through Sensitive Information Neutralization

    Yang, Cheng; Liu, Jixi*; Yan, Yunhe; Shi, Chuan

  87. LaneGraph2Seq: Lane Topology Extraction with Language Model via Vertex-Edge Encoding and Connectivity Enhancement

    Peng, Renyuan; Cai, Xinyue; Xu, Hang; Lu, Jiachen; Wen, Feng; Zhang, Wei; Zhang, Li*

  88. Graph Neural Networks with Soft Association between Topology and Attribute

    Yang, Yachao*; Sun, Yanfeng; Wang, Shaofan; Guo, Jipeng; Gao, Junbin; Ju, Fujiao; Yin, Baocai

  89. No prejudice! Fair Federated Graph Neural Networks for Personalized Recommendation

    Agrawal, Nimesh*; Sirohi, Anuj Kumar; Kumar, Sandeep Prof.; Jayadeva, Jayadeva

  90. KGTS: Contrastive Trajectory Similarity Learning over Prompt Knowledge Graph Embedding

    Chen, Zhen; Zhang, Dalin; Feng, Shanshan; Chen, Kaixuan; Chen, Lisi; Han, Peng; Shang, Shuo*

  91. SAT-based Algorithms for Regular Graph Pattern Matching

    Terra-Neves, Miguel*; Amaral, José; Lemos, Alexandre; Quintino, Rui Dias; Resende, Pedro; Alegria, Antonio

  92. ReGCL: Rethinking Message Passing in Graph Contrastive Learning

    Ji, Cheng*; Huang, Zixuan zi; Sun, Qingyun; Peng, Hao; Fu, Xingcheng; Li, Qian; Li, Jianxin

  93. Multimodal Graph Neural Architecture Search Under Distribution Shifts

    Cai, Jie*; Wang, Xin; Li, Haoyang; Zhang, Ziwei; Zhu, Wenwu

  94. Self-Interpretable Graph Learning with Sufficient and Necessary Explanations

    Deng, Jiale; Shen, Yanyan*

  95. Graph-Shot Prompting: Solving Elaborate Problems in Large Language Models

    Besta, Maciej*; Blach, Nils; Kubicek, Ales; Gerstenberger, Robert; Podstawski, Michal; Gianinazzi, Lukas; Gajda, Joanna; Lehmann, Tomasz; Niewiadomski, Hubert; Nyczyk, Piotr; Hoefler, Torsten

  96. SpaceGTN: A Time-Agnostic Graph Transformer Network for Handwritten Diagram Recognition and Segmentation

    hu, haoxiang*; Gao, Cangjun; Li, YaoKun; Deng, Xiaoming; Lai, Yukun; Ma, Cuixia; Liu, Yong-Jin; Wang, Hongan

  97. Editing Language Model-based Knowledge Graph Embeddings

    Cheng, Siyuan; Zhang, Ningyu*; Tian, Bozhong; Chen, Xi; Liu, Qingbin; Chen, Huajun

  98. Barely Supervised Learning for Graph-based Fraud Detection

    Yu, Hang*; Liu, Zhengyang; Luo, Xiangfeng

  99. Federated Graph Learning under Domain Shift with Generalizable Prototypes

    Wan, Guancheng; Huang, Wenke; Ye, Mang*

  100. CK12: A Rounded K12 Knowledge Graph Based Benchmark for Chinese Holistic Cognition Evaluation

    You, Weihao*; Wang, Pengcheng; Li, Changlong; ji, zhilong; Bai, Jinfeng

  101. GAMC: An Unsupervised Method for Fake News Detection using Graph Autoencoder with Masking

    Yin, Shu; Zhu, Peican; Wu, Lianwei; Gao, Chao*; Wang, Zhen

  102. GraFITi: Graphs for Forecasting Irregularly Sampled Time Series

    Yalavarthi, Vijaya Krishna*; Madhusudhanan, Kiran; Scholz, Randolf; Ahmed, Nourhan; Burchert, Johannes; Jawed, Shayan; Born, Stefan; Schmidt-Thieme, Lars

  103. DAG-Aware Variational Autoencoder for Social Propagation Graph Generation

    Hou, Dongpeng; Gao, Chao*; Li, Xuelong; Wang, Zhen

  104. ASWT-SGNN: Adaptive Spectral Wavelet Transform-based Self-Supervised Graph Neural Network

    Liu, Ruyue; Yin, Rong*; Liu, Yong; Wang, Weiping

  105. A Goal Interaction Graph Planning Framework for Conversational Recommendation

    Zhang, Xiaotong*; jia, xuefang; Liu, Han; Liu, Xinyue; Zhang, Xianchao

  106. Continuous-time Graph Representation with Sequential Survival Process

    Celikkanat, Abdulkadir*; Nakis, Nikolaos; Mørup, Morten

  107. Emotion Rendering for Conversational Speech Synthesis with Heterogeneous Graph-Based Context Modeling

    Liu, Rui*; Hu, Yifan; Ren, Yi; Yin, Xiang; Li, Haizhou

  108. Coupling Graph Neural Networks with Non- Integer Order Dynamics: A Robustness Study

    ZHAO, KAI*; Kang, Qiyu; Song, Yang; XIE, YIHANG; ZHAO, YANAN; Wang, Sijie; She, Rui; Tay, Wee Peng

  109. Dynamic Semantic-based Spatial Graph Convolution Network for Skeleton-based Human Action Recognition

    Xie, Jianyang*; Meng, Yanda; Zhao, Yitian; Nguyen, Anh; yang, xiaoyun; Zheng, Yalin

  110. Span Graph Transformer for Document-level Named Entity Recognition

    Mao, Hongli*; Mao, Xian-Ling; Tang, Hanlin; Shang, Yu-Ming; Huang, Heyan

  111. KGDM: A Diffusion Model to Capture Multiple Relation Semantics for Knowledge Graph Embedding

    long, xiao; Zhuang, Liansheng*; Li, Aodi; Wei, Jiuchang; Li, Houqiang; wang, shafei

  112. Heterogeneous Graph Reasoning for Fact Checking over Texts and Tables

    Gong, Haisong*; Xu, Weizhi; Wu, Shu; Liu, Qiang; Wang, Liang

  113. BOK-VQA: Bilingual Outside Knowledge-based Visual Question Answering via Graph Representation Pretraining

    Kim, Minjun; Song, SeungWoo; Lee, Youhan; Jang, Haneol; Lim, KyungTae*

  114. Optimal Quasi-clique: Hardness, equivalence with Densest-$k$-Subgraph, and quasi- partitioned community mining

    Konar, Aritra*; Sidiropoulos, Nicholas D

  115. KG-TREAT: Pre-training for Treatment Effect Estimation by Synergizing Patient Data with Knowledge Graphs

    Liu, Ruoqi*; Wu, Lingfei; Zhang, Ping

  116. Spear and Shield: Adversarial Attacks and Defense Methods for Model-Based Link Prediction on Continuous-Time Dynamic Graphs

    Lee, Dongjin; Lee, Juho; Shin, Kijung*

  117. Learning Efficient and Robust Multi-agent Communication via Graph Information Bottleneck

    Ding, Shifei*; du, wei; Ding, Ling; Guo, Lili; Zhang, Jian

  118. TopoGCL: Topological Graph Contrastive Learning

    Chen, Yuzhou*; Frias, Jose; Gel, Yulia R.

  119. Spatio-Temporal Fusion for Human Action Recognition via Joint Trajectory Graph

    Zheng, Yaolin; Huang, Hongbo*; wang, xiuying; Yan, Xiaoxu; Xu, Longfei

  120. Towards the disappearing truth: Fine-grained joint causal influences learning with hidden variable-driven causal hypergraphs

    Zhu, Kun*; Zhao, Chunhui

  121. Mixed Geometry Message and Trainable Convolutional Attention Network for Knowledge Graph Completion

    Shang, Bin; Zhao, Yinliang*; Liu, Jun; Wang, Di

  122. GCNext: Towards the Unity of Graph Convolutions for Human Motion Prediction

    Wang, Xinshun; Cui, Qiongjie; Chen, Chen; Liu, Mengyuan*

  123. Hypergraph Neural Architecture Search

    Lin, Wei; Peng, Xu; Yu, Zhengtao; Jin, Taisong*

  124. Graph Disentangled Contrastive Learning with Personalized Transfer for Cross-Domain Recommendation

    Liu, Jing*; Sun, Lele; Nie, Weizhi; Jing, Peiguang; Su, Yu-ting

  125. ROG_PL: Robust Open-Set Graph Learning via Region-based Prototype learning

    ZHANG, QIN*; Lu, Jiexin; Li, Xiaowei; Qiu, Liping; Pan, Shirui; Chen, Xiaojun; Chen, Junyang

  126. DGCLUSTER: A Neural Framework For Attributed Graph Clustering via Modularity Maximization

    Bhowmick, Aritra*; Kosan, Mert; Huang, Zexi; Singh, Ambuj K; Medya, Sourav

  127. Design Graph Guided Element Importance- aware Layout generation with Multi-modality Cascade Transformer

    Zhang, Qiuyun; Guo, Bin*; Yao, Lina; Wang, Hao; Qiao, Xiaotian; Zhang, Ying; Yu, Zhiwen

  128. Full-body Motion Reconstruction with Sparse Sensing from Graph Perspective

    Yao, Feiyu*; Wu, Zongkai; Yi, Li

  129. LLMRG: Improving Recommendations through Large Language Model Reasoning Graphs

    Wang, Yan; Chu, Zhixuan*; Ouyang, Xin; Wang, Simeng; hao, hongyan; Shen, Yue; Gu, Jinjie; Xue, Siqiao; Zhang, James Y; Cui, Qing; li, longfei; Zhou, Jun; Li, Sheng

  130. GIN-SD: Source Detection in Graphs with Incomplete Nodes via Positional Encoding and Attentive Fusion

    Cheng, Le; Zhu, Peican*; Tang, Keke; Gao, Chao; Wang, Zhen

  131. Spectral-based Graph Neutral Networks for Complementary Item Recommendation

    Luo, Haitong*; Meng, Xuying; Wang, Suhang; Cao, Hanyun; zhang, weiyao wei; Wang, Yequan; Zhang, Yujun

  132. Self-supervised Multi-modal Knowledge Graph Contrastive Hashing for Cross-Modal Search

    Liang, Meiyu*; Du, Junping; Liang, Zhengyang; Xing, Yongwang; wei, huang; Xue, Zhe

  133. LGMRec: Local and Global Graph Learning for Multimodal Recommendation

    Guo, Zhiqiang; Li, Jianjun*; Li, Guohui; Wang, Chaoyang; Shi, Si; Ruan, Bin

  134. Mitigating Large Language Model Hallucinations via Autonomous Knowledge Graph-based Retrofitting

    Guan, Xinyan*; liu, yanjiang; Lin, Hongyu; Lu, Yaojie; He, Ben; Han, Xianpei; Sun, Le

  135. Graph Learning in 4D: a Quaternion-valued Laplacian to Enhance Spectral GCNs

    Fiorini, Stefano*; Coniglio, Stefano; Ciavotta, Michele; Messina, Enza

  136. Knowledge Graph Error Detection with Contrastive Confidence Adaption

    Liu, Xiangyu*; Liu, Yang; Hu, Wei

  137. Graph-based Prediction and Planning Policy Network (GP3Net) for scalable self-driving in dynamic environments using Deep Reinforcement Learning

    Chowdhury, Jayabrata*; Shivaraman, Venkataramanan; Sundaram, Suresh; PB, Sujit

  138. Graph Contrastive Invariant Learning from the Causal Perspective

    Wang, Xiao; Mo, Yanhu*; Fan, Shaohua; Shi, Chuan

  139. Discrete Cycle-Consistency based Unsupervised Deep Graph Matching

    Tourani, Siddharth*; Khan, Muhammad Haris; Rother, Carsten; Savchynskyy, Bogdan

  140. Residual Hyperbolic Graph Convolution Networks

    Xue, Yangkai; Dai, Jindou; Lu, Zhipeng*; Wu, Yuwei; Jia, Yunde

  141. Tensorized Label Learning on Anchor Graph

    Li, Jing; Gao, Quanxue; Wang, Qianqian*; Xia, Wei

  142. Rethinking Propagation for Unsupervised Graph Domain Adaptation

    Liu, Meihan*; Fang, Zeyu; Zhang, Zhen; Gu, Ming; Zhou, Sheng; Wang, Xin; Bu, Jiajun

  143. Modeling Knowledge Graphs with Composite Reasoning

    Cui, Wanyun*; Zhang, Linqiu

  144. A Generalized Neural Diffusion Framework on Graphs

    Li, Yibo*; Wang, Xiao; Liu, Hongrui; Shi, Chuan

  145. Transitivity-Preserving Graph Representation Learning for Bridging Local Connectivity and Role-based Similarity

    Hoang, Van Thuy*; Lee, O-Joun

  146. Adaptive Graph Learning for Multimodal Conversational Emotion Detection

    Tu, Geng; Xie, Tian; Liang, Bin; Wang, Hongpeng; Xu, Ruifeng*

  147. Hypergraph Joint Representation Learning for Hypervertices and Hyperedges via Cross Expansion

    Yan, Yuguang; Chen, Yuanlin Chen; Wang, Shibo; Wu, Hanrui; Cai, Ruichu*

  148. Coreference Graph Guidance for Mind-Map Generation

    Zhang, Zhuowei; Hu, Mengting*; Bai, Yinhao; Zhang, Zhen

  149. You Only Read Once: Constituency-Oriented Relational Graph Convolutional Network for Multi-Aspect Multi-Sentiment Classification

    Zheng, Yongqiang; li, xia*

  150. DiG-In-GNN: Discriminative Feature Guided GNN-based Fraud Detector against Inconsistencies in Multi-Relation Fraud Graph

    Zhang, Jinghui; Xu, Zhengjia*; Lv, Dingyang; Shi, Zhan; Shen, Dian; Jin, Jiahui; Dong, Fang

  151. Spatio-Temporal Pivotal Graph Neural Networks for Traffic Flow Forecasting

    Kong, Weiyang; Guo, Ziyu; Liu, Yubao*

  152. Limited Query Graph Connectivity Test

    Guo, Mingyu*; Li, Jialiang; Neumann, Aneta; Neumann, Frank; Nguyen, Hung

  153. Beyond Entities: A Large-Scale Multi-Modal Knowledge Graph with Triplet Fact Grounding

    Liu, Jingping*; Zhang, Mingchuan; Li, Weichen; Wang, Chao; Li, Shuang; Jiang, Haiyun; Jiang, Sihang; Xiao, Yanghua; Chen, Yunwen

  154. Empowering Dual-Level Graph Self-Supervised Pretraining with Motif Discovery

    YAN, Pengwei; Song, Kaisong; Jiang, Zhuoren*; Kang, Yangyang; lin, tianqianjin; Sun, Changlong; Liu, Xiaozhong

  155. Dependency Structure-Enhanced Graph Attention Networks for Event Detection

    Wan, Qizhi*; wan, Changxuan; Xiao, Keli; Lu, Kun; Li, Chenliang; Liu, Xiping; Liu, Dexi

  156. GLDL: Graph Label Distribution Learning

    Jin, Yufei; Gao, Richard; He, Yi; Zhu, Xingquan*

  157. Graph Invariant Learning with Subgraph Co- mixup for Out-Of-Distribution Generalization

    Jia, Tianrui*; Li, Haoyang; Yang, Cheng; Tao, Tao; Shi, Chuan

  158. Data-augmented Curriculum Graph Neural Architecture Search Under Distribution Shifts

    Yao, Yang*; Wang, Xin; Qin, Yijian; Zhang, Ziwei; Zhu, Wenwu; Mei, Hong

  159. Poincar'e Differentially Private for Hierarchy- aware Graph Emebedding

    Wei, Yuecen*; Yuan, Haonan; Fu, Xingcheng; Sun, Qingyun; Peng, Hao; Li, Xianxian; Hu, Chunming

  160. Recurrent Graph Neural Networks and Their Connections to Bisimulation and Logic

    Pflüger, Maximilian*; Tena Cucala, David J; Kostylev, Egor V.

  161. Improved Graph Contrastive Learning for Short Text Classification

    Liu, Yonghao; Huang, Lan; Giunchiglia, Fausto; Feng, Xiaoyue*; Guan, Renchu

  162. Hypergraph-Guided Disentangled Spectrum Transformer Networks for Near-Infrared Facial Expression Recognition

    Luo, Bingjun*; Wang, Haowen; Wang, Jinpeng; Zhu, Junjie; Zhao, Xibin ; Gao, Yue

  163. Spatial-Temporal Interplay in Human Mobility: A Hierarchical Reinforcement Learning Approach with Hypergraph Representation

    Zhang, Zhaofan; Xiao, Yanan; Jiang, Lu; Yang, Dingqi; Yin, Minghao; Wang, Pengyang*

  164. Signed Graph Neural Ordinary Differential Equation for Modeling Continuous-time Dynamics

    Chen, Lanlan; WU, KAI*; Lou, Jian; Liu, Jing

  165. Graph Neural Prompting for Question Answering with Large Language Models

    Tian, Yijun; Song, Huan*; Wang, Zichen; Wang, Haozhu; Hu, Ziqing; Wang, Fang; Chawla, Nitesh; Xu, Panpan

  166. Revisiting Graph-based Fraud Detection in Sight of Heterophily and Spectrum

    Xu, Fan mark*; Wang, Nan; Wu, Hao; Wen, Xuezhi; Zhao, Xibin; Wan, Hai

  167. Towards Effective and General Graph Unlearning via Mutual Evolution

    Li, Xunkai*; Zhao, Yulin; Wu, Zhengyu; Zhang, Wentao; Li, Ronghua; Wang, Guoren

  168. Explainable Origin-Destination Crowd Flow Interpolation via Variational Multi-modal Recurrent Graph Auto-Encoder

    Zhou, Qiang; Lu, Xinjiang*; Gu, Jingjing; Zheng, Zhe; Jin, Bo; Zhou, Jingbo

  169. Embedded Feature Selection on Graph-based Multi-view Clustering

    Li, Guangfei; Yang, Haizhou; Gao, Quanxue; Wang, Qianqian*; Zhao, Wenhui

  170. MKG-FENN: A Multimodal Knowledge Graph Fused End-to-end Neural Network for Accurate Drug–Drug Interaction Prediction

    Wu, Di*; wu, sun; He, Yi; Chen, Zhong; Luo, Xin

  171. Learning to Reweight for Generalizable Graph Neural Network

    Chen, Zhengyu*; Xiao, Teng ; Kuang, Kun; Lv, Zheqi; Zhang, Min; Yang, Jinluan; Lu, Chengqiang; Yang, Hongxia; Wu, Fei

  172. Measuring Task Similarity and Its Implication in Fine-Tuning Graph Neural Networks

    Huang, Renhong; Xu, Jiarong*; Jiang, Xin; Pan, Chenglu; Yang, Zhiming; Wang, Chunping; Yang, Yang

  173. Towards Fair Graph Federated Learning via Incentive Mechanisms

    Pan, Chenglu; Xu, Jiarong*; Yu, Yue; Yang, Ziqi; Wu, Qingbiao; Wang, Chunping; CHEN, Lei; Yang, Yang

  174. Value at Adversarial Risk: A Graph Defense Strategy Against Cost-Aware Attacks

    Liao, Junlong; Fu, Wenda; Wang, Cong; Wei, Zhongyu; Xu, Jiarong*

  175. A Joint Framework with Heterogeneous- Relation-Aware Graph and Multi-Channel Label Enhancing Strategy for Event Causality Extraction

    Pu, Ruili; Li, Yang; Zhao, Jun; Wang, Suge*; Li, Deyu; Liao, Jian; Zheng, Jianxing

  176. Bayesian Inference with Complex Knowledge Graph Evidence

    Toroghi, Armin*; Sanner, Scott

  177. Structural Information Enhanced Graph Representation for Link Prediction

    Shi, Lei*; Hu, Bin; Zhao, Deng; He, Jianshan; Zhang, Zhiqiang; Zhou, Jun

  178. Anchoring Path for Inductive Relation Prediction in Knowledge Graphs

    Su, Zhixiang*; Wang, Di; Miao, Chunyan; Cui, Lizhen

  179. R3CD: Scene Graph to Image Generation with Relation-aware Compositional Contrastive Control Diffusion

    Liu, Jinxiu*; Liu, Qi

  180. HGPrompt: Bridging Homogeneous and Heterogeneous Graphs for Few-shot Prompt Learning

    Yu, Xingtong*; Fang, Yuan; Liu, Zemin; Zhang, Xinming

  181. Structural Entropy Based Graph Structure Learning for Node Classification

    Duan, Liang; xiang, chen; Wenjie, Liu; Liu, Daliang; Yue, Kun*; Li, Angsheng

  182. SimCalib: Graph Neural Network Calibration based on Similarity Between Nodes

    Tang, Boshi*; Wu, Zhiyong; Wu, Xixin; Huang, Qiaochu; Chen, Jun; Lei, Shun; Meng, Helen

  183. A Twist for Graph Classification: Optimizing Causal Information Flow in Graph Neural Networks

    Zhao, Zhe; Wang, Pengkun; Wen , HaiBin; Zhang, Yudong; Zhou, Zhengyang ; Wang, Yang*

  184. Fully-Connected Spatial-Temporal Graph for Multivariate Time Series Data

    Wang, Yucheng*; Xu, Yuecong; Yang, Jianfei; Wu, Min; Li, Xiaoli; Xie, Lihua; Chen, Zhenghua

  185. Data Augmented Graph Neural Networks for Personality Detection

    Zhu, Yangfu; Xia, Yue; Li, Meiling; Zhang, Tingting; Wu, Bin*

  186. LAFA: Multimodal Knowledge Graph Completion with Link Aware Fusion and Aggregation

    Shang, Bin; Zhao, Yinliang*; Liu, Jun; Wang, Di

  187. Fine-tuning Graph Neural Networks by Preserving Graph Generative Patterns

    Sun, Yifei*; Zhu, Qi; Yang, Yang; Wang, Chunping; Fan, Tianyu; Zhu, Jiajun; CHEN, Lei

  188. Complete Neural Networks for Complete Euclidean Graphs

    hordan, snir*; Amir, Tal; Dym, Nadav; Gortler, Steven

  189. Progressive Distillation based on Masked Generation Feature Method for Knowledge Graph Completion

    Fan, Cunhang*; Chen, Yujie; Xue, Jun; kong, yonghui; tao, jianhua; lv, zhao

  190. Dynamic Spiking Graph Neural Networks

    Nan, Yin*; Wang, Mengzhu; Chen, Zhenghan; De Masi, Giulia; Xiong, Huan; Gu, Bin

  191. G-Adapter: Towards Structure-Aware Parameter-Efficient Transfer Learning for Graph Transformer Networks

    Gui, Anchun*; Ye, Jinqiang; Xiao, Han

  192. Higher-order Graph Convolutional Network with Flower-Petals Laplacians on Simplicial Complexes

    Huang, Yiming*; Zeng, Yujie; Wu, Qiang; Lü, Linyuan

  193. Finite-Time Frequentist Regret Bounds of Multi- Agent Thompson Sampling on Sparse Hypergraphs

    Jin, Tianyuan*; Hsu, Hao-Lun; Chang, William; Xu, Pan

  194. Unknown-Aware Graph Regularization for Robust Semi-Supervised Learning from Uncurated Data

    Kong, Heejo*; Kim, Suneung; Kim, Ho-Joong; Lee, Seong-Whan

  195. A Graph Dynamics Prior for Relational Inference

    Pan, Liming*; Shi, Cheng; Dokmanic, Ivan

  196. Towards Streaming Spatial-Temporal Graph Learning: A Decoupled Perspective

    Wang, Binwu; Wang, Pengkun; Zhang, Yudong; Wang, Xu; Zhou, Zhengyang ; Bai, Lei; Wang, Yang*

  197. Hierarchical Topology Isomorphism Expertise Embedded Graph Contrastive Learning

    Li, Jiangmeng; Jin, Yifan; Gao, Hang; Qiang, Wenwen*; Zheng, Changwen; Sun, Fuchun

  198. Scores for Learning Discrete Causal Graphs with Unobserved Confounders

    Bellot, Alexis*; Zhang, Junzhe; Bareinboim, Elias

  199. Provably Powerful Graph Neural Networks for Directed Multigraphs

    Egressy, Beni*; von Niederhäusern, Luc; Blanuša, Jovan; Altman, Erik; Wattenhofer, Roger; Atasu, Kubilay

  200. Multi-Modal Discussion Transformer: Integrating Text, Images and Graph Transformers to Detect Hate Speech on Social Media

    Hebert, Liam*; Sahu, Gaurav; Guo, Yuxuan; Sreenivas, Nanda Kishore; Golab, Lukasz; Cohen, Robin

  201. Graph Bayesian Optimization for Multiplex Influence Maximization

    Yuan, Zirui; Shao, Minglai*; Chen, Zhiqian

  202. Multiple-Source Localization from a Single- Snapshot Observation Using Graph Bayesian Optimization

    Zhang, Zonghan*; Zhang, Zijian; Chen, Zhiqian

  203. T-NET: Weakly Supervised Graph Learning for Combatting Human Trafficking

    Nair, Pratheeksha*; Liu, Javin; Vajiac, Catalina; Olligschlaeger, Andreas; Chau, Duen Horng; Cazzolato, Mirela; Jones, Cara; Faloutsos, Christos; Rabbany, Reihaneh

  204. Fair Graph Learning Using Constraint-aware Priority Adjustment and Graph Masking in River Networks

    He, Erhu*; Xie, Yiqun; Sun, Alexander Y; Zwart, Jacob; Yang, Jie; Jin, Zhenong; Wang, Yang; Karimi, Hassan; Jia, Xiaowei

  205. Physics-Informed Graph Neural Networks for Water Distribution Systems

    Ashraf, Inaam*; Strotherm, Janine; Hermes, Luca; Hammer, Barbara

  206. Multi-Modal Discussion Transformer: Integrating Text, Images and Graph Transformers to Detect Hate Speech on Social Media

    Hebert, Liam*; Sahu, Gaurav; Guo, Yuxuan; Sreenivas, Nanda Kishore; Golab, Lukasz; Cohen, Robin

  207. Graph Bayesian Optimization for Multiplex Influence Maximization

    Yuan, Zirui; Shao, Minglai*; Chen, Zhiqian

  208. Multiple-Source Localization from a Single- Snapshot Observation Using Graph Bayesian Optimization

    Zhang, Zonghan*; Zhang, Zijian; Chen, Zhiqian

  209. T-NET: Weakly Supervised Graph Learning for Combatting Human Trafficking

    Nair, Pratheeksha*; Liu, Javin; Vajiac, Catalina; Olligschlaeger, Andreas; Chau, Duen Horng; Cazzolato, Mirela; Jones, Cara; Faloutsos, Christos; Rabbany, Reihaneh

  210. Fair Graph Learning Using Constraint-aware Priority Adjustment and Graph Masking in River Networks

    He, Erhu*; Xie, Yiqun; Sun, Alexander Y; Zwart, Jacob; Yang, Jie; Jin, Zhenong; Wang, Yang; Karimi, Hassan; Jia, Xiaowei

  211. Physics-Informed Graph Neural Networks for Water Distribution Systems

    Ashraf, Inaam*; Strotherm, Janine; Hermes, Luca; Hammer, Barbara

  212. PreRoutGNN for Timing Prediction with Order Preserving Partition: Global Circuit Pre-training, Local Signal Delay Learning and Attentional Cell Modeling

    Zhong, Ruizhe*; Ye, Junjie; Tang, Zhentao; Kai, Shixiong; Yuan, Mingxuan; Hao, Jianye; Yan, Junchi

  213. DGA-GNN: Dynamic Grouping Aggregation GNN for Fraud Detection

    Duan, Mingjiang; Zheng, Tongya; Gao, Yang; Wang, Gang; Feng, Zunlei*; Wang, Xinyu

  214. AdapterGNN: Parameter-Efficient Fine-Tuning Improves Generalization in GNNs

    Li, Shengrui; Han, Xueting*; Bai, Jing

  215. DR-Label: Label Deconstruction and Reconstruction of GNN Models for Catalysis Systems

    Wang, Bowen*; Liang, Chen; Wang, Jiaze; Qiu, Jiezhong; Liu, Furui; HAO, SHAOGANG; Li, Dong; Chen, Guangyong; Zou, Xiaolong; Heng, Pheng- Ann

  216. Prot2Text: Multimodal Protein’s Function Generation with GNNs and Transformers

    Abdine, Hadi*; Chatzianastasis, Michail; Bouyioukos, Costas; Vazirgiannis, Michalis

  217. Improving GNN Calibration with Discriminative Ability: Insights and Strategies

    Fang, Yujie; Li, Xin*; Chen, QIanyu; Wang, Mingzhong

  218. Stratified GNN Explanations through Sufficient Expansion

    Ji, Yuwen*; Shi, Lei; liu, zhimeng; Wang, Ge

  219. Curriculum-Enhanced Residual Soft An-Isotropic Normalization for Over-smoothness in Deep GNNs

    Li, Jin; Zhang, Qirong; Xu, Shuling; Chen, Xinlong; Guo, Longkun l; Fu, Yang-Geng*

  1. Self-supervised Graph Disentangled Networks for Review-based Recommendation

    Yuyang Ren, Haonan Zhang, Qi Li, Luoyi Fu, Xinbing Wang, Chenghu Zhou

  2. A Canonicalization-Enhanced Known Fact-Aware Framework For Open Knowledge Graph Link Prediction

    Yilin Wang, Minghao Hu, Zhen Huang, Dongsheng Li, Wei Luo, Dong Yang, Xicheng Lu

  3. KDLGT: A Linear Graph Transformer Framework via Kernel Decomposition Approach

    Yi Wu, Yanyang Xu, Wenhao Zhu, Guojie Song, Zhouchen Lin, Liang Wang, Shaoguo Liu

  4. Multi-level Graph Contrastive Prototypical Clustering

    Yuchao Zhang, Yuan Yuan, Qi Wang

  5. Graph Propagation Transformer for Graph Representation Learning

    Zhe Chen, Hao Tan, Tao Wang, Tianrun Shen, Tong Lu, Qiuying Peng, Cheng Cheng, Yue Qi

  6. Graph Sampling-based Meta-Learning for Molecular Property Prediction

    Xiang Zhuang, Qiang Zhang, Bin Wu, Keyan Ding, Yin Fang, Huajun Chen

  7. A Unification Framework for Euclidean and Hyperbolic Graph Neural Networks

    Mehrdad khatir, Nurendra Choudhary, Sutanay Choudhury, Khushbu Agarwal, Chandan K Reddy

  8. PPAT: Progressive Graph Pairwise Attention Network for Event Causality Identification

    Zhenyu Liu, Baotian Hu, Zhenran Xu, Min Zhang

  9. Violin: Virtual Overbridge Linking for Enhancing Semi-supervised Learning on Graphs with Limited Labels

    Siyue Xie, Da Sun Handason Tam, Wing Cheong Lau

  10. Hierarchical Transformer for Scalable Graph Learning

    Wenhao Zhu, Tianyu Wen, Guojie Song, Xiaojun Ma, Liang Wang

  11. Basket Representation Learning by Hypergraph Convolution on Repeated Items for Next-basket Recommendation

    Yalin Yu, Enneng Yang, Guibing Guo, Linying Jiang, Xingwei Wang

  12. Totally Dynamic Hypergraph Neural Networks

    Peng Zhou, Zongqian Wu, Xiangxiang Zeng, Guoqiu Wen, Junbo Ma, Xiaofeng Zhu

  13. Gapformer: Graph Transformer with Graph Pooling for Node Classification

    Chuang Liu, Yibing Zhan, Xueqi Ma, Liang Ding, Dapeng Tao, Jia Wu, Wenbin Hu

  14. One Model, Any CSP: Graph Neural Networks as Fast Global Search Heuristics for Constraint Satisfaction

    Jan Tönshoff, Berke Kisin, Jakob Lindner, Martin Grohe

  15. Continuous-Time Graph Learning for Cascade Popularity Prediction

    Xiaodong Lu, Shuo Ji, Le Yu, Leilei Sun, Bowen Du, Tongyu Zhu

  16. CSGCL: Community-Strength-Enhanced Graph Contrastive Learning

    Han Chen, Ziwen Zhao, Yuhua Li, Yixiong Zou, Ruixuan Li, Rui Zhang

  17. Enabling Abductive Learning to Exploit Knowledge Graph

    Yu-Xuan Huang, Zequn Sun, Guangyao Li, Xiaobin Tian, Wang-Zhou Dai, Wei Hu, Yuan Jiang, Zhi-Hua Zhou

  18. CONGREGATE: Contrastive Graph Clustering in Curvature Spaces

    Li Sun, Feiyang Wang, Junda Ye, Hao Peng, Philip S. Yu

  19. LGI-GT: Graph Transformers with Local and Global Operators Interleaving

    Shuo Yin, Guoqiang Zhong

  20. An Ensemble Approach for Automated Theorem Proving Based on Efficient Name Invariant Graph Neural Representations

    Achille Fokoue, Ibrahim Abdelaziz, Maxwell Crouse, Shajith Ikbal, Akihiro Kishimoto, Guilherme Lima, Ndivhuwo Makondo, Radu Marinescu

  21. MolHF: A Hierarchical Normalizing Flow for Molecular Graph Generation

    Yiheng Zhu, Zhenqiu Ouyang, Ben Liao, Jialu Wu, Yixuan Wu, Chang-Yu Hsieh, Tingjun Hou, Jian Wu

  22. LSGNN: Towards General Graph Neural Network in Node Classification by Local Similarity

    Yuhan Chen, Yihong Luo, Jing Tang, Liang Yang, Siya Qiu, Chuan Wang, Xiaochun Cao

  23. Globally Consistent Federated Graph Autoencoder for Non-IID Graphs

    Kun Guo, Yutong Fang, Qingqing Huang, Yuting Liang, Ziyao Zhang, Wenyu He, Liu Yang, Kai Chen, Ximeng Liu, Wenzhong Guo

  24. SemiGNN-PPI: Self-Ensembling Multi-Graph Neural Network for Efficient and Generalizable Protein–Protein Interaction Prediction

    Ziyuan Zhao, Peisheng Qian, Xulei Yang, Zeng Zeng, Cuntai Guan, Wai Leong Tam, Xiaoli Li

  25. Minimizing Reachability Times on Temporal Graphs via Shifting Labels

    Argyrios Deligkas, Eduard Eiben, George Skretas

  26. Beyond Homophily: Robust Graph Anomaly Detection via Neural Sparsification

    Zheng Gong, Guifeng Wang, Ying Sun, Qi Liu, Yuting Ning, Hui Xiong, Jingyu Peng

  27. SAD: Semi-Supervised Anomaly Detection on Dynamic Graphs

    Sheng Tian, Jihai Dong, Jintang Li, WENLONG ZHAO, Xiaolong Xu, Baokun Wang, Bowen Song, Changhua Meng, Tianyi Zhang, Liang Chen

  28. Graph Neural Convection-Diffusion with Heterophily

    KAI ZHAO, Qiyu Kang, Yang Song, Rui She, Sijie Wang, Wee Peng Tay

  29. Semi-supervised Domain Adaptation in Graph Transfer Learning

    Ziyue Qiao, Xiao Luo, Meng Xiao, Hao Dong, Yuanchun Zhou, Hui Xiong

  30. Multi-Scale Subgraph Contrastive Learning

    Yanbei Liu, Yu Zhao, Xiao Wang, Lei Geng, Zhitao Xiao

  31. Multi-view Contrastive Learning Hypergraph Neural Network for Drug-Microbe-Disease Association Prediction

    Luotao Liu, Feng Huang, Xuan Liu, Zhankun Xiong, Menglu Li, Congzhi Song, Wen Zhang

  32. Multi-View Robust Graph Representation Learning for Graph Classification

    Guanghui Ma, Chunming Hu, Ling Ge, Hong Zhang

  33. Graph-based Semi-supervised Local Clustering with Few Labeled Nodes

    Zhaiming Shen, Ming-Jun Lai, Sheng Li

  34. Adaptive Path-Memory Network for Temporal Knowledge Graph Reasoning

    Hao Dong, Zhiyuan Ning, Pengyang Wang, Ziyue Qiao, Pengfei Wang, Yuanchun Zhou, Yanjie Fu

  35. FedHGN: A Federated Framework for Heterogeneous Graph Neural Networks

    Xinyu Fu, Irwin King

  36. Intent-aware Recommendation via Disentangled Graph Contrastive Learning

    Yuling Wang, Xiao Wang, Xiangzhou Huang, Yanhua Yu, Haoyang Li, Mengdi Zhang, Zirui Guo, Wei Wu

  37. Doubly Stochastic Graph-based Non-autoregressive Reaction Prediction

    Ziqiao Meng, Peilin Zhao, Yang Yu, Irwin King

  38. Causal-Based Supervision of Attention in Graph Neural Network: A Better and Simpler Choice towards Powerful Attention

    Hongjun Wang, Jiyuan Chen, Lun Du, Qiang Fu, Shi Han, Xuan Song

  1. A Generalization of ViT/MLP-Mixer to Graphs

    Xiaoxin He, Bryan Hooi, Thomas Laurent, Adam Perold, Yann LeCun, Xavier Bresson

  2. A Gromov--Wasserstein Geometric View of Spectrum-Preserving Graph Coarsening

    Yifan Chen, Rentian Yao, Yun Yang, Jie Chen

  3. Additive Causal Bandits with Unknown Graph

    Alan Malek, Virginia Aglietti, Silvia Chiappa

  4. Alternately Optimized Graph Neural Networks

    Haoyu Han, Xiaorui Liu, Haitao Mao, MohamadAli Torkamani, Feng Shi, Victor Lee, Jiliang Tang

  5. Boosting Graph Contrastive Learning via Graph Contrastive Saliency

    Chunyu Wei, Yu Wang, Bing Bai, Kai Ni, David J. Brady, LU FANG

  6. ClusterFuG: Clustering Fully connected Graphs by Multicut

    Ahmed Abbas, Paul Swoboda

  7. CoCo: A Coupled Contrastive Framework for Unsupervised Domain Adaptive Graph Classification

    Nan Yin, Li Shen, Mengzhu Wang, Long Lan, Zeyu Ma, Chong Chen, Xian-Sheng Hua, Xiao Luo

  8. Conditional Graph Information Bottleneck for Molecular Relational Learning

    Namkyeong Lee, Dongmin Hyun, Gyoung S. Na, Sungwon Kim, Junseok Lee, Chanyoung Park

  9. D2Match: Leveraging Deep Learning and Degeneracy for Subgraph Matching

    Xuanzhou Liu, Lin Zhang, Jiaqi Sun, Yujiu Yang, Haiqin Yang

  10. DRew: Dynamically Rewired Message Passing with Delay

    Benjamin Gutteridge, Xiaowen Dong, Michael M. Bronstein, Francesco Di Giovanni

  11. Dink-Net: Neural Clustering on Large Graphs

    Yue Liu, KE LIANG, Jun Xia, sihang zhou, Xihong Yang, Xinwang Liu, Stan Z. Li

  12. Disentangled Multiplex Graph Representation Learning

    Yujie Mo, Yajie Lei, Jialie Shen, Xiaoshuang Shi, Heng Tao Shen, Xiaofeng Zhu

  13. Distribution Free Prediction Sets for Node Classification

    Jase Clarkson

  14. Do Not Train It: A Linear Neural Architecture Search of Graph Neural Networks

    Peng XU, Lin Zhang, Xuanzhou Liu, Jiaqi Sun, Yue Zhao, Haiqin Yang, Bei Yu

  15. ED-Batch: Efficient Automatic Batching of Dynamic Neural Networks via Learned Finite State Machines

    Siyuan Chen, Pratik Pramod Fegade, Tianqi Chen, Phillip Gibbons, Todd Mowry

  16. Efficient Algorithms for Exact Graph Matching on Correlated Stochastic Block Models with Constant Correlation

    Joonhyuk Yang, Dongpil Shin, Hye Won Chung

  17. Efficient Learning of Mesh-Based Physical Simulation with Bi-Stride Multi-Scale Graph Neural Network

    Yadi Cao, Menglei Chai, Minchen Li, Chenfanfu Jiang

  18. Efficient and Degree-Guided Graph Generation via Discrete Diffusion Modeling

    Xiaohui Chen, Jiaxing He, Xu Han, Liping Liu

  19. Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian

    Haiyang Yu, Zhao Xu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji

  20. Ewald-based Long-Range Message Passing for Molecular Graphs

    Arthur Kosmala, Johannes Gasteiger, Nicholas Gao, Stephan Günnemann

  21. Exphormer: Sparse Transformers for Graphs

    Hamed Shirzad, Ameya Velingker, Balaji Venkatachalam, Danica J. Sutherland, Ali Kemal Sinop

  22. Fast Online Node Labeling for Very Large Graphs

    Baojian Zhou, Yifan Sun, Reza Babanezhad Harikandeh

  23. Featured Graph Coarsening with Similarity Guarantees

    Manoj Kumar, Anurag Sharma, Shashwat Saxena, Sandeep Kumar

  24. Finding the Missing-half: Graph Complementary Learning for Homophily-prone and Heterophily-prone Graphs

    YIZHEN ZHENG, He Zhang, Vincent Lee, Yu Zheng, Xiao Wang, Shirui Pan

  25. Fisher Information Embedding for Node and Graph Learning

    Dexiong Chen, Paolo Pellizzoni, Karsten Borgwardt

  26. From Hypergraph Energy Functions to Hypergraph Neural Networks

    Yuxin Wang, Quan Gan, Xipeng Qiu, Xuanjing Huang, David Wipf

  27. From Relational Pooling to Subgraph GNNs: A Universal Framework for More Expressive Graph Neural Networks

    Cai Zhou, Xiyuan Wang, Muhan Zhang

  28. GC-Flow: A Graph-Based Flow Network for Effective Clustering

    Tianchun Wang, Farzaneh Mirzazadeh, Xiang Zhang, Jie Chen

  29. GNN&GBDT-Guided Fast Optimizing Framework for Large-scale Integer Programming

    Huigen Ye, Hua Xu, Hongyan Wang, Chengming Wang, Yu Jiang

  30. GREAD: Graph Neural Reaction-Diffusion Networks

    Jeongwhan Choi, Seoyoung Hong, Noseong Park, Sung-Bae Cho

  31. Generated Graph Detection

    Yihan Ma, Zhikun Zhang, Ning Yu, Xinlei He, Michael Backes, Yun Shen, Yang Zhang

  32. Graph Contrastive Backdoor Attacks

    Hangfan Zhang, Jinghui Chen, Lu Lin, Jinyuan Jia, Dinghao Wu

  33. Graph Generative Model for Benchmarking Graph Neural Networks

    Minji Yoon, Yue Wu, John Palowitch, Bryan Perozzi, Russ Salakhutdinov

  34. Graph Inductive Biases in Transformers without Message Passing

    Liheng Ma, Chen Lin, Derek Lim, Adriana Romero-Soriano, Puneet K. Dokania, Mark Coates, Philip Torr, Ser-Nam Lim

  35. Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate Communication

    AJAY KUMAR JAISWAL, Shiwei Liu, Tianlong Chen, Ying Ding, Zhangyang Wang

  36. Graph Mixup with Soft Alignments

    Hongyi Ling, Zhimeng Jiang, Meng Liu, Shuiwang Ji, Na Zou

  37. Graph Neural Networks can Recover the Hidden Features Solely from the Graph Structure

    Ryoma Sato

  38. Graph Neural Networks with Learnable and Optimal Polynomial Bases

    Yuhe Guo, Zhewei Wei

  39. Graph Neural Tangent Kernel: Convergence on Large Graphs

    Sanjukta Krishnagopal, Luana Ruiz

  40. Graph Positional Encoding via Random Feature Propagation

    Moshe Eliasof, Fabrizio Frasca, Beatrice Bevilacqua, Eran Treister, Gal Chechik, Haggai Maron

  41. GraphCleaner: Detecting Mislabelled Samples in Popular Graph Learning Benchmarks

    Yuwen Li, Miao Xiong, Bryan Hooi

  42. HOPE: High-order Graph ODE For Modeling Interacting Dynamics

    Xiao Luo, Jingyang Yuan, Zijie Huang, Huiyu Jiang, Yifang Qin, Wei Ju, Ming Zhang, Yizhou Sun

  43. Half-Hop: A graph upsampling approach for slowing down message passing

    Mehdi Azabou, Venkataramana Ganesh, Shantanu Thakoor, Chi-Heng Lin, Lakshmi Sathidevi, Ran Liu, Michal Valko, Petar Veličković, Eva L Dyer

  44. Hierarchical Grammar-Induced Geometry for Data-Efficient Molecular Property Prediction

    Minghao Guo, Veronika Thost, Samuel W Song, Adithya Balachandran, Payel Das, Jie Chen, Wojciech Matusik

  45. Implicit Graph Neural Networks: A Monotone Operator Viewpoint

    Justin Baker, Qingsong Wang, Cory D Hauck, Bao Wang

  46. Improving Graph Generation by Restricting Graph Bandwidth

    Nathaniel Lee Diamant, Alex Tseng, Kangway V Chuang, Tommaso Biancalani, Gabriele Scalia

  47. Improving Graph Neural Networks with Learnable Propagation Operators

    Moshe Eliasof, Lars Ruthotto, Eran Treister

  48. InGram: Inductive Knowledge Graph Embedding via Relation Graphs

    Jaejun Lee, Chanyoung Chung, Joyce Jiyoung Whang

  49. LazyGNN: Large-Scale Graph Neural Networks via Lazy Propagation

    Rui Xue, Haoyu Han, MohamadAli Torkamani, Jian Pei, Xiaorui Liu

  50. Learning the Right Layers a Data-Driven Layer-Aggregation Strategy for Semi-Supervised Learning on Multilayer Graphs

    Sara Venturini, Andrea Cristofari, Francesco Rinaldi, Francesco Tudisco

  51. Leveraging Label Non-Uniformity for Node Classification in Graph Neural Networks

    Feng Ji, See Hian Lee, Hanyang Meng, Kai Zhao, Jielong Yang, Wee Peng Tay

  52. Linkless Link Prediction via Relational Distillation

    Zhichun Guo, William Shiao, Shichang Zhang, Yozen Liu, Nitesh Chawla, Neil Shah, Tong Zhao

  53. Local Vertex Colouring Graph Neural Networks

    Shouheng Li, Dongwoo Kim, Qing Wang

  54. Modeling Dynamic Environments with Scene Graph Memory

    Andrey Kurenkov, Michael Lingelbach, Tanmay Agarwal, Emily Jin, Chengshu Li, Ruohan Zhang, Li Fei-Fei, Jiajun Wu, Silvio Savarese, Roberto Martín-Martín

  55. Multi-class Graph Clustering via Approximated Effective $p$-Resistance

    Shota Saito, Mark Herbster

  56. Node Embedding from Neural Hamiltonian Orbits in Graph Neural Networks

    Qiyu Kang, Kai Zhao, Yang Song, Sijie Wang, Wee Peng Tay

  57. On Heterogeneous Treatment Effects in Heterogeneous Causal Graphs

    Richard A Watson, Hengrui Cai, Xinming An, Samuel McLean, Rui Song

  58. On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology

    Francesco Di Giovanni, Lorenzo Giusti, Federico Barbero, Giulia Luise, Pietro Lio, Michael M. Bronstein

  59. On the Connection Between MPNN and Graph Transformer

    Chen Cai, Truong Son Hy, Rose Yu, Yusu Wang

  60. On the Expressive Power of Geometric Graph Neural Networks

    Chaitanya K. Joshi, Cristian Bodnar, Simon V Mathis, Taco Cohen, Pietro Lio

  61. One-Shot Compression of Large Edge-Exchangeable Graphs using Bits-Back Coding

    Daniel Severo, James Townsend, Ashish J Khisti, Alireza Makhzani

  62. Online Learning with Feedback Graphs: The True Shape of Regret

    Tomáš Kocák, Alexandra Carpentier

  63. PLay: Parametrically Conditioned Layout Generation using Latent Diffusion

    Chin-Yi Cheng, Forrest Huang, Gang Li, Yang Li

  64. Path Neural Networks: Expressive and Accurate Graph Neural Networks

    Gaspard Michel, Giannis Nikolentzos, Johannes F. Lutzeyer, Michalis Vazirgiannis

  65. Personalized Subgraph Federated Learning

    Jinheon Baek, Wonyong Jeong, Jiongdao Jin, Jaehong Yoon, Sung Ju Hwang

  66. Randomized Schur Complement Views for Graph Contrastive Learning

    Vignesh Kothapalli

  67. Reducing SO(3) Convolutions to SO(2) for Efficient Equivariant GNNs

    Saro Passaro, C. Lawrence Zitnick

  68. Relevant Walk Search for Explaining Graph Neural Networks

    Ping Xiong, Thomas Schnake, Michael Gastegger, Grégoire Montavon, Klaus Robert Muller, Shinichi Nakajima

  69. Rethinking Explaining Graph Neural Networks via Non-parametric Subgraph Matching

    Fang Wu, Siyuan Li, Xurui Jin, Yinghui Jiang, Dragomir Radev, Zhangming Niu, Stan Z. Li

  70. Revisiting Over-smoothing and Over-squashing Using Ollivier-Ricci Curvature

    Khang Nguyen, Nong Minh Hieu, Vinh Duc NGUYEN, Nhat Ho, Stanley Osher, Tan Minh Nguyen

  71. Rotation and Translation Invariant Representation Learning with Implicit Neural Representations

    Sehyun Kwon, Joo Young Choi, Ernest K. Ryu

  72. SEGA: Structural Entropy Guided Anchor View for Graph Contrastive Learning

    Junran Wu, Xueyuan Chen, Bowen Shi, Shangzhe Li, Ke Xu

  73. Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learning

    Taoan Huang, Aaron M Ferber, Yuandong Tian, Bistra Dilkina, Benoit Steiner

  74. SlotGAT: Slot-based Message Passing for Heterogeneous Graphs

    Ziang Zhou, Jieming Shi, Renchi Yang, Yuanhang Zou, Qing Li

  75. Theoretical Bounds on the Network Community Profile from Low-rank Semi-definite Programming

    Yufan Huang, C. Seshadhri, David F. Gleich

  76. Tight and fast generalization error bound of graph embedding in metric space

    Atsushi Suzuki, Atsushi Nitanda, Taiji Suzuki, jing wang, Feng Tian, Kenji Yamanishi

  77. Towards Better Graph Representation Learning with Parameterized Decomposition & Filtering

    Mingqi Yang, Wenjie Feng, Yanming Shen, Bryan Hooi

  78. Towards Deep Attention in Graph Neural Networks: Problems and Remedies

    Soo Yong Lee, Fanchen Bu, Jaemin Yoo, Kijung Shin

  79. Towards Robust Graph Incremental Learning on Evolving Graphs

    Junwei Su, Difan Zou, Zijun Zhang, Chuan Wu

  80. Towards Understanding and Reducing Graph Structural Noise for GNNs

    Mingze Dong, Yuval Kluger

  81. Transformers Meet Directed Graphs

    Simon Geisler, Yujia Li, Daniel J Mankowitz, Ali Taylan Cemgil, Stephan Günnemann, Cosmin Paduraru

  82. Understanding Oversquashing in GNNs through the Lens of Effective Resistance

    Mitchell Black, Zhengchao Wan, Amir Nayyeri, Yusu Wang

  83. Vertical Federated Graph Neural Network for Recommender System

    Peihua Mai, Yan Pang

  84. WL meet VC

    Christopher Morris, Floris Geerts, Jan Tönshoff, Martin Grohe

  85. Wasserstein Barycenter Matching for Graph Size Generalization of Message Passing Neural Networks

    Xu Chu, Yujie Jin, Xin Wang, Shanghang Zhang, Yasha Wang, Wenwu Zhu, Hong Mei

  86. Which Invariance Should We Transfer? A Causal Minimax Learning Approach

    Mingzhou Liu, Xiangyu Zheng, Xinwei Sun, Fang Fang, Yizhou Wang

  1. Kernel Ridge Regression-Based Graph Dataset Distillation

    Zhe Xu, Yuzhong Chen, Menghai Pan, Huiyuan Chen, Mahashweta Das, Hao Yang, Hanghang Tong

  2. Reducing Exposure to Harmful Content via Graph Rewiring

    Corinna Coupette, Stefan Neumann, Aristides Gionis

  3. Community-based Dynamic Graph Learning for Popularity Prediction

    Shuo Ji, Xiaodong Lu, Mingzhe Liu, Leilei Sun, Chuanren Liu, Bowen Du, Hui Xiong

  4. GetPt: Graph-enhanced General Table Pre-training with Alternate Attention Network

    Ran Jia, Haoming Guo, Xiaoyuan Jin, Chao Yan, Lun Du, Xiaojun Ma, Tamara Stankovic, Marko Lozajic, Goran Zoranovic, Igor Ilic, Shi Han, Dongmei Zhang

  5. Empower Post-hoc Graph Explanations with Information Bottleneck: A Pre-training and Fine-tuning Perspective

    Jihong Wang, Minnan Luo, Jundong Li, Yun Lin, Yushun Dong, Jin Song Dong, Qinghua Zheng

  6. MixupExplainer: Generalizing Explanations for Graph Neural Networks with Data Augmentation

    Jiaxing Zhang, Dongsheng Luo, Hua Wei

  7. Pyramid Graph Neural Network: A Graph Sampling and Filtering Approach for Multi-Scale Disentangled Representations

    Haoyu Geng, Chao Chen, Yixuan He, Gang Zeng, Zhaobing Han, Hua Chai, Junchi Yan

  8. What’s Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders

    Jintang Li, Ruofan Wu, Wangbin Sun, Liang Chen, Sheng Tian, Liang Zhu, Changhua Meng, Zibin Zheng, Weiqiang Wang

  9. Efficient and Effective Edge-Wise Graph Representation Learning

    Hewen Wang, Renchi Yang, Keke Huang, Xiaokui Xiao

  10. Towards Graph-Level Anomaly Detection via Deep Evolutionary Mapping

    Xiaoxiao Ma, Jia Wu, Jian Yang, Quan Z. Sheng

  11. VQNE: Variational Quantum Network Embedding with Application to Network Alignment

    Xinyu Ye, Ge Yan, Junchi Yan

  12. CARL-G: Clustering-Accelerated Representation Learning on Graphs

    William Shiao, Uday Singh Saini, Yozen Liu, Tong Zhao, Neil Shah, Evangelos E. Papalexakis

  13. On Improving the Cohesiveness of Graphs by Merging Nodes: Formulation, Analysis, and Algorithms

    Fanchen Bu, Kijung Shin

  14. Densest Diverse Subgraphs: How to Plan a Successful Cocktail Party with Diversity

    Atsushi Miyauchi, Tianyi Chen, Konstantinos Sotiropoulos, Charalampos E. Tsourakakis

  15. Localised Adaptive Spatial-Temporal Graph Neural Network

    Wenying Duan, Xiaoxi He, Zimu Zhou, Lothar Thiele, Hong Rao

  16. PERT-GNN: Latency Prediction for Microservice-Based Cloud-Native Applications via Graph Neural Networks

    Da Sun Handason Tam, Yang Liu, Huanle Xu, Siyue Xie, Wing Cheong Lau

  17. Causal Effect Estimation on Hierarchical Spatial Graph Data

    Koh Takeuchi, Ryo Nishida, Hisashi Kashima, Masaki Onishi

  18. Improving the Expressiveness of K-hop Message-Passing GNNs by Injecting Contextualized Substructure Information

    Tianjun Yao, Yingxu Wang, Kun Zhang, Shangsong Liang

  19. On Structural Expressive Power of Graph Transformers

    Wenhao Zhu, Tianyu Wen, Guojie Song, Liang Wang, Bo Zheng

  20. MGNN: Graph Neural Networks Inspired by Distance Geometry Problem

    Guanyu Cui, Zhewei Wei

  21. Improving Expressivity of GNNs with Subgraph-specific Factor Embedded Normalization

    Kaixuan Chen, Shunyu Liu, Tongtian Zhu, Ji Qiao, Yun Su, Yingjie Tian, Tongya Zheng, Haofei Zhang, Zunlei Feng, Jingwen Ye, Mingli Song

  22. Learning Strong Graph Neural Networks with Weak Information

    Yixin Liu, Kaize Ding, Jianling Wang, Vincent Lee, Huan Liu, Shirui Pan

  23. Clenshaw Graph Neural Networks

    Yuhe Guo, Zhewei Wei

  24. All in One: Multi-Task Prompting for Graph Neural Networks

    Xiangguo Sun, Hong Cheng, Jia Li, Bo Liu, Jihong Guan

  25. Certified Edge Unlearning for Graph Neural Networks

    Kun Wu, Jie Shen, Yue Ning, Ting Wang, Wendy Hui Wang

  26. Augmenting Recurrent Graph Neural Networks with a Cache

    Guixiang Ma, Vy A Vo, Theodore L. Willke, Nesreen K. Ahmed

  27. Narrow the Input Mismatch in Deep Graph Neural Network Distillation

    Qiqi Zhou, Yanyan Shen, Lei Chen

  28. Sketch-Based Anomaly Detection in Streaming Graphs

    Siddharth Bhatia, Mohit Wadhwa, Kenji Kawaguchi, Neil Shah, Philip Yu, Bryan Hooi

  29. Knowledge Graph Reasoning over Entities and Numerical Values

    Jiaxin Bai, Chen Luo, zheng li, Qingyu Yin, Bing Yin, Yangqiu Song

  30. Exploiting Relation-Aware Attribute Representation Learning in Knowledge Graph Embedding for Numerical Reasoning

    Gayeong Kim, Sookyung Kim, Ko Keun Kim, Suchan Park, Heesoo Jung, Hogun Park

  31. AdaProp: Learning Adaptive Propagation for Graph Neural Network based Knowledge Graph Reasoning

    Yongqi Zhang, Zhanke Zhou, Quanming Yao, Xiaowen Chu, Bo Han

  32. Context-Aware Event Forecasting via Graph Disentanglement

    Yunshan Ma, Chenchen Ye, Zijian Wu, Xiang Wang, Yixin Cao, Tat-seng Chua

  33. Representation Learning on Hyper-Relational and Numeric Knowledge Graphs with Transformers

    Chanyoung Chung, Jaejun Lee, Joyce Jiyoung Whang

  34. GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks

    Wentao Zhao, Qitian Wu, Chenxiao Yang, Junchi Yan

  35. Grace: Graph Self-Distillation and Completion to Mitigate Degree-Relatednesses

    Hui Xu, Liyao Xiang, Femke Huang, Yuting Weng, Ruijie Xu, Xinbing Wang, Chenghu Zhou

  36. GraphSHA: Synthesizing Harder Samples for Class-Imbalanced Node Classification

    Wen-Zhi Li, Chang-Dong Wang, Hui Xiong; The Hong Kong University of Science and Technology), Jian-Huang Lai

  37. Classification of Edge-Dependent Labels of Nodes in Hypergraphs

    Minyoung Choe, Sunwoo Kim, Jaemin Yoo, Kijung Shin

  38. Enhancing Graph Representations Learning with Decorrelated Propagation

    Hua Liu, Wei Jin, Xiaorui Liu, Hui Liu

  39. Meta Graph Learning for Long-Tail Recommendation

    Chunyu Wei, Jian Liang, Di Liu, Zehui Dai, Mang Li, Fei Wang

  40. Graph Neural Bandits

    Yunzhe Qi, Yikun Ban, Jingrui He

  41. E-commerce Search via Content Collaborative Graph Neural Network

    Guipeng Xv, Chen Lin, Wanxian Guan, Jinping Gou, Xubin Li, Hongbo Deng, Jian Xu, Bo Zheng

  42. Criteria Tell You More than Ratings: Criteria Preference-Aware Light Graph Convolution for Effective Multi-Criteria Recommendation

    Jin-Duk Park, Siqing Li, Xin Cao, Won-Yong Shin

  43. Knowledge Graph Self-Supervised Rationalization for Recommendation

    Yuhao Yang, Chao Huang, Lianghao Xia, Chunzhen Huang

  44. On Manipulating Signals of User-Item Graph: A Jacobi Polynomial-based Graph Collaborative Filtering

    Jiayan Guo, Lun Du, Xu Chen, Xiaojun Ma, Qiang Fu, Shi Han, Dongmei Zhang, Yan Zhang

  45. Incremental Causal Graph Learning for Online Root Cause Analysis

    Dongjie Wang, Zhengzhang Chen, Yanjie Fu, Yanchi Liu, Haifeng Chen

  46. Transferable Graph Structure Learning for Graph-Based Traffic Forecasting Across Cities

    Yilun Jin, Kai Chen, Qiang Yang

  47. FLAMES2Graph: An Interpretable Federated Multivariate Time Series Classification Framework

    Raneen Younis, Zahra Ahmadi, Abdul Hakmeh, Marco Fisichella

  48. Joint Pre-training and Local Re-training: Transferable Representation Learning on Multi-Source Knowledge Graphs

    Zequn Sun, Jiacheng Huang, Jinghao Lin, Xiaozhou Xu, Qijin Chen, Wei Hu

  49. Recognizing Unseen Objects via Multimodal Intensive Knowledge Graph Propagation

    Likang Wu, Zhi Li, Hongke Zhao, Zhefeng Wang, Qi Liu, Baoxing Huai, Nicholas Jing Yuan, Enhong Chen

  50. Few-Shot Low-Resource Knowledge Graph Completion with Multi-view Task Representation Generation

    Shichao Pei, Ziyi Kou, Qiannan Zhang, Xiangliang Zhang

  51. Hyperbolic Graph Topic Modeling Network with Continuously Updated Topic Tree

    Delvin Ce Zhang, Rex Ying, Hady W. Lauw

  52. PROSE: Graph Structure Learning via Progressive Strategy

    Huizhao Wang, Yao Fu, Tao Yu, Linghui Hu, Weihao Jiang, Shiliang Pu

  53. Less is More: SlimG for Accurate, Robust, and Interpretable Graph Mining

    Jaemin Yoo, Meng-Chieh Lee, Shubhranshu Shekhar, Christos Faloutsos

  54. Task-Equivariant Graph Few-Shot Learning

    Sungwon Kim, Junseok Lee, Namkyeong Lee, Wonjoong Kim, Seungyoon Choi, Chanyoung Park

  55. GAT-MF: Graph Attention Mean Field for Very Large Scale Multi-Agent Reinforcement Learning

    Qianyue Hao, Wenzhen Huang, Tao Feng, Jian Yuan, Yong Li

  56. Networked Time Series Imputation via Position-aware Graph Enhanced Variational Autoencoders

    Dingsu Wang, Yuchen Yan, Ruizhong Qiu, Yada Zhu, Kaiyu Guan, Andrew Margenot, Hanghang Tong

  57. DECOR: Degree-Corrected Social Graph Refinement for Fake News Detection

    Jiaying Wu, Bryan Hooi

  58. FLOOD: A Flexible Invariant Learning Framework for Out-of-Distribution Generalization on Graphs

    Yang Liu, Xiang Ao, Fuli Feng, Yunshan Ma, Kuan Li, Tat-seng Chua, Qing He

  59. A Data-centric Framework to Endow Graph Neural Networks with Out-Of-Distribution Detection Ability

    Yuxin Guo, Cheng Yang, Yuluo Chen, Jixi Liu, Chuan Shi, Junping Du

  60. Financial Default Prediction via Motif-Preserving Graph Neural Network with Curriculum Learning

    Daixin Wang, Zhiqiang Zhang, Yeyu Zhao, Kai Huang, Yulin Kang, Jun Zhou

  61. Towards Reliable Rare Category Analysis on Graphs via Individual Calibration

    Longfeng Wu, Bowen Lei, Dongkuan Xu, Dawei Zhou

  62. QTIAH-GNN: Quantity and Topology Imbalance-Aware Heterogeneous Graph Neural Network for Bankruptcy Prediction

    Yucheng Liu, Zipeng Gao, Xiangyang Liu, Pengfei Luo, Yang Yang, Hui Xiong; The Hong Kong University of Science and Technology

  63. Multiplex Heterogeneous Graph Neural Network with Behavior Pattern Modeling

    Chaofan Fu, Guanjie Zheng, Chao Huang, Yanwei Yu, Junyu Dong

  64. Locality Sensitive Hashing for Optimizing Subgraph Query Processing in Parallel Computing Systems

    Peng Peng, Shengyi Ji, Zhen Tian, Hongbo Jiang, Weiguo Zheng, Xuecang Zhang

  65. Efficient Distributed Approximate k-Nearest Neighbor Graph Construction by Multiway Random Division Forest

    Sang-Hong Kim, Ha-Myung Park

  66. Accelerating Dynamic Network Embedding with Billions of Parameter Updates to Milliseconds

    Haoran Deng, Yang Yang, Jiahe Li, Haoyang Cai, Shiliang Pu, Weihao Jiang

  67. DyTed: Disentangled Representation Learning for Discrete-Time Dynamic Graph

    Kaike Zhang, Qi Cao, Gaolin Fang, Xu Bingbing, Hongjian Zou, Huawei Shen, Xueqi Cheng

  68. Counterfactual Learning on Heterogeneous Graphs with Greedy Perturbation

    Qiang Yang, Changsheng Ma, Qiannan Zhang, Xin Gao, Chuxu Zhang, Xiangliang Zhang

  69. WinGNN: Dynamic Graph Neural Networks with Random Gradient Aggregation Window

    Yifan Zhu, Fangpeng Cong, Dan Zhang, Wenwen Gong, Qika Lin, Wenzheng Feng, Yuxiao Dong, Jie Tang

  70. EXTRACT and REFINE: Finding a Support Subgraph Set for Graph Representation

    Kuo Yang, Zhengyang Zhou, Wei Sun, Pengkun Wang, Xu Wang, Yang Wang

  71. Using Motif Transitions for Temporal Graph Generation

    Penghang Liu, Ahmet Erdem Sariyuce

  72. Interpretable Sparsification of Brain Graphs: Better Practices and Effective Designs for Graph Neural Networks

    Gaotang Li, Marlena Duda, Xiang Zhang, Danai Koutra, Yujun Yan

  73. Enhancing Node-Level Adversarial Defenses by Lipschitz Regularization of Graph Neural Networks

    Yaning Jia, Dongmian Zou, Hongfei Wang, Hai Jin

  74. Temporal Dynamics-Aware Adversarial Attacks on Discrete-Time Dynamic Graph Models

    Kartik Sharma, Rakshit Trivedi, Rohit Sridhar, Srijan Kumar

  75. A Unified Framework of Graph Information Bottleneck for Robustness and Membership Privacy

    Enyan Dai, Limeng Cui, Zhengyang Wang, Xianfeng Tang, Yinghan Wang, Monica Cheng, Bing Yin, Suhang Wang

  76. Pattern Expansion and Consolidation on Evolving Graphs for Continual Traffic Prediction

    Binwu Wang, Yudong Zhang, Xu Wang, Pengkun Wang, Zhengyang Zhou, LEI BAI, Yang Wang

  77. Spatial Heterophily Aware Graph Neural Networks

    Congxi Xiao, Jingbo Zhou, Jizhou Huang, Tong Xu, Hui Xiong; The Hong Kong University of Science and Technology

  78. Leveraging Relational Graph Neural Network for Transductive Model Ensemble

    Zhengyu Hu, Jieyu Zhang, Haonan Wang, Siwei Liu, Shangsong Liang

  79. When to Pre-Train Graph Neural Networks? From Data Generation Perspective!

    Yuxuan Cao, Jiarong Xu, Carl Yang, Jiaan Wang, Yunchao Zhang, Chunping Wang, Lei CHEN, Yang Yang

  80. Boosting Multitask Learning on Graphs through Higher-Order Task Affinities

    Dongyue Li, Haotian Ju, Aneesh Sharma, Hongyang R. Zhang

  81. Graph Neural Processes for Spatio-Temporal Extrapolation

    Junfeng Hu, Yuxuan Liang, Zhencheng Fan, Hongyang Chen, Yu Zheng, Roger Zimmermann

  82. Reconstructing Graph Diffusion History from a Single Snapshot

    Ruizhong Qiu, Dingsu Wang, Lei Ying, H. Vincent Poor, Yifang Zhang, Hanghang Tong

  83. Generalizing Graph ODE for Learning Complex System Dynamics across Environments

    Zijie Huang, Yizhou Sun, Wei Wang

  84. B2-Sampling: Fusing Balanced and Biased Sampling for Graph Contrastive Learning

    Mengyue Liu, Yun Lin, Jun Liu, Bohao Liu, Qinghua Zheng, Jin Song Dong

  85. Similarity Preserving Adversarial Graph Contrastive Learning

    Yeonjun In, Kanghoon Yoon, Chanyoung Park

  86. HomoGCL: Rethinking Homophily in Graph Contrastive Learning

    Wen-Zhi Li, Chang-Dong Wang, Hui Xiong; The Hong Kong University of Science and Technology), Jian-Huang Lai

  87. Contrastive Cross-scale Graph Knowledge Synergy

    Yifei Zhang, Yankai Chen, Zixing Song, Irwin King

  88. Graph Contrastive Learning with Generative Adversarial Network

    Cheng Wu, Chaokun Wang, Jingcao Xu, Ziyang Liu, Kai Zheng, Xiaowei Wang, Yang Song, Kun Gai

  89. BatchSampler: Sampling Mini-Batches for Contrastive Learning in Vision, Language, and Graphs

    Zhen Yang, Tinglin Huang, Ming Ding, Yuxiao Dong, Rex Ying, Yukuo Cen, Yangliao Geng, Jie Tang

  90. GMOCAT: A Graph-Enhanced Multi-Objective Method for Computerized Adaptive Testing

    Hangyu Wang, Ting Long, Liang Yin, Weinan Zhang, Wei Xia, Qichen Hong, Dingyin Xia, Ruiming Tang, Yong Yu

  91. Semi-Supervised Graph Imbalanced Regression

    Gang Liu, Tong Zhao, Eric Inae, Tengfei Luo, Meng Jiang

  92. Learning Joint Relational Co-Evolution in Spatial-Temporal Knowledge Graph for SMEs Supply Chain Prediction

    Youru Li, Zhenfeng Zhu, Xiaobo Guo, Linxun Chen, Zhouyin Wang, Yinmeng Wang, Bing Han, Yao Zhao

  93. A Look into Causal Effects under Entangled Treatment in Graphs: Investigating the Impact of Contact on MRSA Infection

    Jing Ma, Chen Chen, Anil Vullikanti, Ritwick Mishra, Gregory Madden, Daniel Borrajo, Jundong Li

  94. Commonsense Knowledge Graph towards Supper APP and Its Applications in Alipay

    Xiaoling Zang, Binbin Hu, Chu Jun, Zhiqiang Zhang, Guannan Zhang, Jun Zhou, Wenliang Zhong

  95. Diga: Guided Diffusion Model for Graph Recovery in Anti-Money Laundering

    Xujia Li, Yuan Li, Xueying Mo, Hebing Xiao, Yanyan Shen, Lei Chen; Hong Kong University of Science and Technology

  96. DGI: An Easy and Efficient Framework for GNN Model Evaluation

    Peiqi Yin, Xiao Yan, Jinjing Zhou, Qiang Fu, Zhenkun Cai, James Cheng, Bo Tang, Minjie Wang

  97. Learning Multivariate Hawkes Process via Graph Recurrent Neural Network

    Kanghoon Yoon, Youngjun Im, Jingyu Choi, Taehwan Jeong, Jinkyoo Park

  98. HUGE: Huge Unsupervised Graph Embeddings with TPUs

    Brandon A. Mayer, Anton Tsitsulin, Hendrik Fichtenberger, Jonathan Halcrow, Bryan Perozzi

  99. Impact-Oriented Contextual Scholar Profiling using Self-Citation Graphs

    Yuankai Luo, Lei Shi, Mufan Xu, Yuwen Ji, Fengli Xiao, Chunming Hu, Zhiguang Shan

  100. IGB: Addressing The Gaps In Labeling, Features, Heterogeneity, and Size of Public Graph Datasets for Deep Learning Research

    Arpandeep Khatua, Vikram Sharma Mailthody, Bhagyashree Taleka, Tengfei Ma, Xiang Song, Wen-mei Hwu

  101. MIDLG: Mutual Information based Dual Level GNN for Transaction Fraud Complaint Verification

    Wen Zheng, Bingbing Xu, Emiao Lu, Yang Li, Qi Cao, Xuan Zong, Huawei Shen

  102. Graph Learning in Physical-Informed Mesh-Reduced Space for Real-World Dynamic Systems

    Yeping Hu, Bo Lei, Victor M. Castillo

  103. Knowledge Based Prohibited Item Detection on Heterogeneous Risk Graphs

    Tingyan Xiang, Ao Li, Yugang Ji, Dong Li

  104. TrustGeo: Uncertainty-Aware Dynamic Graph Learning for Trustworthy IP Geolocation

    Wenxin Tai, Bin Chen, Fan Zhou, Ting Zhong, Goce Trajcevski, Yong Wang, Kai Chen

  105. Expert Knowledge-Aware Image Difference Graph Representation Learning for Difference-Aware Medical Visual Question Answering

    Xinyue Hu, Lin Gu, Qiyuan An, Zhang Mengliang, Liangchen Liu, Kazuma Kobayashi, Tatsuya Harada, Ronald M. Summers, Yingying Zhu

  106. Graph-Based Model-Agnostic Data Subsampling for Recommendation Systems

    Xiaohui Chen, Jiankai Sun, Taiqing Wang, Ruocheng Guo, Li-Ping Liu, Aonan Zhang

  107. Graph-Aware Language Model Pre-Training on a Large Graph Corpus Can Help Multiple Graph Applications

    Han Xie, Da Zheng, Jun Ma, Houyu Zhang, Vassilis N. Ioannidis, Xiang Song, Qing Ping, Sheng Wang, Carl Yang, Yi Xu, Belinda Zeng, Trishul Chilimbi

  108. PGLBox: Multi-GPU Graph Learning Framework for Web-Scale Recommendation

    Xuewu Jiao, Weibin Li, Xinxuan Wu, Wei Hu, Miao Li, Jiang Bian, Siming Dai, Xinsheng Luo, Mingqing Hu, Zhengjie Huang, Danlei Feng, Junchao Yang, Shikun Feng, Haoyi Xiong, Dianhai Yu, Shuanglong Li, Jingzhou He, Yanjun Ma, Lin Liu

  109. Adaptive Graph Contrastive Learning for Recommendation

    Yangqin Jiang, Chao Huang, Lianghao Xia

  110. Real Time Index and Search Across Large Quantities of GNN Experts For Low Latency Online Learning

    Johan Zhi Kang Kok, Sien Yi Tan, Bingsheng He, Zhen Zhang

  111. ILRoute: A Graph-based Imitation Learning Method to Unveil Riders’ Routing Strategies in Food Delivery Service

    Tao Feng, Huan Yan, Huandong Wang, Wenzhen Huang, Yuyang Han, Hongsen Liao, Jinghua Hao, Yong Li

  112. Deep Transfer Learning for City-Scale Cellular Traffic Generation through Urban Knowledge Graph

    Zhang Shiyuan, Tong Li, Shuodi Hui, Guangyu Li, Yanping Liang, Li Yu, Depeng Jin, Yong Li

  1. Adaptive Graph Representation Learning for Next POI Recommendation

    Zhaobo Wang, Yanmin Zhu, Chunyang Wang, Wenze Ma, Bo Li, Jiadi Yu

  2. Adaptive Popularity Debiasing Aggregator for Graph Collaborative Filtering

    Huachi Zhou, Hao Chen, Junnan Dong, Daochen Zha, Chuang Zhou, Xiao Huang

  3. Candidate–aware Graph Contrastive Learning for Recommendation

    Wei He, Guohao Sun, Jinhu Lu, Xiu Susie Fang

  4. Continual Learning on Dynamic Graphs via Parameter Isolation

    Peiyan Zhang, Yuchen Yan, Chaozhuo Li, Senzhang Wang, Xing Xie, Guojie Song, Sunghun Kim

  5. Contrastive Learning for Signed Bipartite Graphs

    Zeyu Zhang, Jiamou Liu, Kaiqi Zhao, Song Yang, Xianda Zheng, Yifei Wang

  6. Decoupled Hyperbolic Graph Attention Network for Cross-domain Named Entity Recognition

    Jingyun Xu, Yi Cai

  7. Distillation-Enhanced Graph Masked Autoencoders for Bundle Recommendation

    Yuyang Ren, Zhang Haonan, Luoyi Fu, Xinbing Wang, Chenghu Zhou

  8. DREAM: Adaptive Reinforcement Learning based on Attention Mechanism for Temporal Knowledge Graph Reasoning

    Shangfei Zheng, Hongzhi Yin, Tong Chen, Quoc Viet Hung Nguyen, Wei Chen, Lei Zhao

  9. Dynamic Graph Evolution Learning for Recommendation

    Haoran Tang, Shiqing Wu, Guandong Xu, Qing Li

  10. Generative-Contrastive Graph Learning for Recommendation

    Yonghui Yang, Zhengwei Wu, Le Wu, Kun Zhang, Richang Hong, Zhiqiang Zhang, Jun Zhou, Meng Wang

  11. Graph Masked Autoencoder for Sequential Recommendation

    Yaowen Ye, Lianghao Xia, Chao Huang

  12. Knowledge-enhanced Multi-View Graph Neural Networks for Session-based Recommendation

    Qian Chen, Zhiqiang Guo, Jianjun Li, Guohui Li

  13. Learn from Relational Correlations and Periodic Events for Temporal Knowledge Graph Reasoning

    Ke Liang, Lingyuan Meng, Meng Liu, Yue Liu, Wenxuan Tu, Siwei Wang, Sihang Zhou, Xinwang Liu

  14. LightGT: A Light Graph Transformer for Multimedia Recommendation

    Yinwei Wei, Wenqi Liu, Fan Liu, Xiang Wang, Liqiang Nie, Tat-Seng Chua

  15. M2GNN: Metapath and Multi-interest Aggregated Graph Neural Network for Tag-based Cross-domain Recommendation

    Zepeng Huai, Yuji Yang, Mengdi Zhang, Zhongyi Zhang, Yichun Li, Wei Wu

  16. Graph Transformer for Recommendation

    Chaoliu Li, Lianghao Xia, Xubin Ren, Yaowen Ye, Yong Xu, Chao Huang

  17. Mixed-Curvature Manifolds Interaction Learning for Knowledge Graph-aware Recommendation

    Jihu Wang, Yuliang Shi, Han Yu, Xinjun Wang, Zhongmin Yan, Fanyu Kong

  18. Multi-order Matched Neighborhood Consistent Graph Alignment in a Union Vector Space

    Wei Tang, Haifeng Sun, Jingyu Wang, Qi Qi, Jing Wang, Hao Yang, Shimin Tao

  19. Multi-view Hypergraph Contrastive Policy Learning for Conversational Recommendation

    Sen Zhao, Wei Wei, Xian-Ling Mao, Shuai Zhu, Minghui Yang, Zujie Wen, Dangyang Chen, Feida Zhu

  20. Next Basket Recommendation with Intent-aware Hypergraph Adversarial Network

    Ran Li, Liang Zhang, Guannan Liu, Junjie Wu

  21. Normalizing Flow-based Neural Process for Few-Shot Knowledge Graph Completion

    Linhao Luo, Reza Haffari, Yuan Fang Li, Shirui Pan

  22. Relation-Aware Multi-Positive Contrastive Knowledge Graph Completion with Embedding Dimension Scaling

    Bin Shang, Yinliang Zhao, Di Wang, Jun Liu

  23. Schema-aware Reference as Prompt Improves Data-Efficient Knowledge Graph Construction

    Yunzhi Yao, Shengyu Mao, Ningyu Zhang, Xiang Chen, Shumin Deng, Xi Chen, Huajun Chen

  24. Seq-HGNN: Learning Sequential Node Representation on Heterogeneous Graph

    Chenguang Du, Kaichun Yao, Hengshu Zhu, Deqing Wang, Fuzhen Zhuang, Hui Xiong

  25. Session Search with Pre-trained Graph Classification Model

    Shengjie Ma, Chong Chen, Jiaxin Mao, Qi Tian, Xuhui Jiang

  26. Spatio-Temporal Hypergraph Learning for Next POI Recommendation

    Xiaodong Yan, Tengwei Song, Yifeng Jiao, Jianshan He, Jiaotuan Wang, Ruopeng Li, Wei Chu

  27. StreamE: Learning to Update Representations for Temporal Knowledge Graphs in Streaming Scenarios

    Jiasheng Zhang, Jie Shao, Bin Cui

  28. Subgraph Search over Neural-Symbolic Graphs

    Ye Yuan, Delong Ma, Anbiao Wu, Jianbin Qin

  29. Leveraging Transferable Knowledge Concept Graph Embedding for Cold-Start Cognitive Diagnosis

    Weibo Gao, Hao Wang, Qi Liu, Fei Wang, Xin Lin, Linan Yue, Zheng Zhang, Rui Lv, Shijin Wang

  30. Time-interval Aware Share Recommendation via Bi-directional Continuous Time Dynamic Graphs

    Ziwei Zhao, Xi Zhu, Tong Xu, Aakas Lizhiyu, Yu Yu, Xueying Li, Zikai Yin, Enhong Chen

  31. Topic-enhanced Graph Neural Networks for Extraction-based Explainable Recommendation

    Jie Shuai, Le Wu, Kun Zhang, Peijie Sun, Richang Hong, Meng Wang

  32. Weighted Knowledge Graph Embedding

    Zhao Zhang, Zhanpeng Guan, Fuwei Zhang, Fuzhen Zhuang, Zhulin An, Fei Wang, Yongjun Xu

  33. DeviceGPT: A Generative Pre-Training Transformer on the Heterogenous Graph for Internet of Things

    Yimo Ren, Jinfa Wang, Hong Li, Hongsong Zhu, Limin Sun

  34. DocGraphLM: Documental graph language model for information extraction

    Dongsheng Wang, Zhiqiang Ma, Armineh Nourbakhsh, Kang Gu, Sameena Shah

  35. Gated Attention with Asymmetric Regularization for Transformer-based Continual Graph Learning

    Hongxiang Lin, Ruiqi Jia, Xiaoqing Lyu

  36. Graph Collaborative Signals Denoising and Augmentation for Recommendation

    Ziwei Fan, Ke Xu, Zhang Dong, Hao Peng, Jiawei Zhang, Philip S. Yu

  37. Hierarchical Type Enhanced Negative Sampling for Knowledge Graph Embedding

    Zhenzhou Lin, Zishuo Zhao, Jingyou Xie, Ying Shen

  38. HyperFormer: Learning Expressive Sparse Feature Representations via Hypergraphs

    Kaize Ding, Albert Jiongqian Liang, Bryan Perozzi, Ting Chen, Ruoxi Wang, Lichan Hong, Ed H. Chi, Huan Liu, Derek Zhiyuan Cheng

  39. MDKG: Graph-Based Medical Knowledge-Guided Dialogue Generation

    Usman Naseem, Surendrabikram Thapa, Qi Zhang, Liang Hu, Mehwish Nasim

  40. Retrieval-Enhanced Generative Model for Large-Scale Knowledge Graph Completion

    Donghan Yu, Yiming Yang

  41. Sharpness-Aware Graph Collaborative Filtering

    Huiyuan Chen, Chin-Chia Michael Yeh, Yujie Fan, Yan Zheng, Junpeng Wang, Vivian Lai, Mahashweta Das, Hao Yang

  42. TrustSGCN: Learning Trustworthiness on Edge Signs for Effective Signed Graph Convolutional Networks

    Min-Jeong Kim, Yeon-Chang Lee, Sang-Wook Kim

  43. Which Matters Most in Making Fund Investment Decisions? A Multi-granularity Graph Disentangled Learning Framework

    Chunjing Gan, Binbin Hu, Bo Huang, Tianyu Zhao, Yingru Lin, Wenliang Zhong, Zhiqiang Zhang, Jun Zhou, Chuan Shi

  44. WSFE: Wasserstein Sub-graph Feature Encoder for Effective User Segmentation in Collaborative Filtering

    Yankai Chen, Yifei Zhang, Menglin Yang, Zixing Song, Chen Ma, Irwin King

  1. (Provable) Adversarial Robustness for Group Equivariant Tasks: Graphs, Point Clouds, Molecules, and More

    Jan Schuchardt, Yan Scholten, Stephan Günnemann

  2. 4D Panoptic Scene Graph Generation

    Jingkang Yang, Jun CEN, WENXUAN PENG, Shuai Liu, Fangzhou Hong, Xiangtai Li, Kaiyang Zhou, Qifeng Chen, Ziwei Liu

  3. A Comparative Study of Graph Structure Learning: Benchmark and Analysis

    Zhixun Li, Liang Wang, Xin Sun, Yifan Luo, Yanqiao Zhu, Dingshuo Chen, Yingtao Luo, Xiangxin Zhou, Qiang Liu, Shu Wu, Liang Wang, Jeffrey Yu

  4. A Comprehensive Study on Text-attributed Graphs: Benchmarking and Rethinking

    Hao Yan, Chaozhuo Li, Ruosong Long, Chao Yan, Jianan Zhao, Wenwen Zhuang, Jun Yin, Peiyan Zhang, Weihao Han, Hao Sun, Weiwei Deng, Qi Zhang, Lichao Sun, Xing Xie, Senzhang Wang

  5. A Fractional Graph Laplacian Approach to Oversmoothing

    Sohir Maskey, Raffaele Paolino, Aras Bacho, Gitta Kutyniok

  6. A Meta Learning Model for Scalable Hyperbolic Graph Neural Networks

    Nurendra Choudhary, Nikhil Rao, Chandan Reddy

  7. A Metadata-Driven Approach to Understand Graph Neural Networks

    Ting Wei Li, Qiaozhu Mei, Jiaqi Ma

  8. A Neural Collapse Perspective on Feature Evolution in Graph Neural Networks

    Vignesh Kothapalli, Tom Tirer, Joan Bruna

  9. A graphon-signal analysis of graph neural networks

    Ron Levie

  10. A new perspective on building efficient and expressive 3D equivariant graph neural networks

    weitao Du, Yuanqi Du, Limei Wang, Dieqiao Feng, Guifeng Wang, Shuiwang Ji, Carla Gomes, Zhi-Ming Ma

  11. A*Net: A Scalable Path-based Reasoning Approach for Knowledge Graphs

    Zhaocheng Zhu, Xinyu Yuan, Michael Galkin, Louis-Pascal Xhonneux, Ming Zhang, Maxime Gazeau, Jian Tang

  12. AMAG: Additive, Multiplicative and Adaptive Graph Neural Network For Forecasting Neuron Activity

    Jingyuan Li, Leo Scholl, Trung Le, Amy Orsborn, Eli Shlizerman

  13. Accelerating Molecular Graph Neural Networks via Knowledge Distillation

    Filip Ekström Kelvinius, Dimitar Georgiev, Artur Toshev, Johannes Gasteiger

  14. Act As You Wish: Fine-grained Control of Motion Diffusion Model with Hierarchical Semantic Graphs

    Peng Jin, Yang Wu, Yanbo Fan, Zhongqian Sun, Wei Yang, Li Yuan

  15. Adversarial Robustness in Graph Neural Networks: A Hamiltonian Energy Conservation Approach

    Kai Zhao, Yang Song, Qiyu Kang, Rui She, Sijie Wang, Wee Peng Tay

  16. Adversarial Training for Graph Neural Networks

    Lukas Gosch, Simon Geisler, Daniel Sturm, Bertrand Charpentier, Daniel Zügner, Stephan Günnemann

  17. Affinity-Aware Graph Networks

    Ameya Velingker, Ali Sinop, Ira Ktena, Petar Veličković, Sreenivas Gollapudi

  18. An Empirical Study Towards Prompt-Tuning for Graph Contrastive Pre-Training in Recommendations

    Haoran Yang, Xiangyu Zhao, Yicong Li, Hongxu Chen, Guandong Xu

  19. Approximately Equivariant Graph Networks

    Ningyuan Huang, Ron Levie, Soledad Villar

  20. Architecture Matters: Uncovering Implicit Mechanisms in Graph Contrastive Learning

    Xiaojun Guo, Yifei Wang, Zeming Wei, Yisen Wang

  21. AutoGO: Automated Computation Graph Optimization for Neural Network Evolution

    Mohammad Salameh, Keith Mills, Negar Hassanpour, Fred Han, Shuting Zhang, Wei Lu, Shangling Jui, CHUNHUA ZHOU, Fengyu Sun, Di Niu

  22. Bayesian Optimisation of Functions on Graphs

    Xingchen Wan, Pierre Osselin, Henry Kenlay, Binxin Ru, Michael A Osborne, Xiaowen Dong

  23. Better with Less: A Data-Centric Prespective on Pre-Training Graph Neural Networks

    *Jiarong Xu, Renhong Huang, XIN JIANG, Yuxuan Cao, Carl Yang, Chunping Wang, YANG YANG*

  24. Beyond Exponential Graph: Communication-Efficient Topologies for Decentralized Learning via Finite-time Convergence

    Yuki Takezawa, Ryoma Sato, Han Bao, Kenta Niwa, Makoto Yamada

  25. CAT-Walk: Inductive Hypergraph Learning via Set Walks

    Ali Behrouz, Farnoosh Hashemi, Sadaf Sadeghian, Margo Seltzer

  26. Calibrate and Boost Logical Expressiveness of GNN Over Multi-Relational and Temporal Graphs

    Yeyuan Chen, Dingmin Wang

  27. Can Language Models Solve Graph Problems in Natural Language?

    Heng Wang, Shangbin Feng, Tianxing He, Zhaoxuan Tan, Xiaochuang Han, Yulia Tsvetkov

  28. Certifiably Robust Graph Contrastive Learning

    Minhua Lin, Teng Xiao, Enyan Dai, Xiang Zhang, Suhang Wang

  29. Characterization and Learning of Causal Graphs with Small Conditioning Sets

    Murat Kocaoglu

  30. Characterizing Graph Datasets for Node Classification: Homophily-Heterophily Dichotomy and Beyond

    Oleg Platonov, Denis Kuznedelev, Artem Babenko, Liudmila Prokhorenkova

  31. CommonScenes: Generating Commonsense 3D Indoor Scenes with Scene Graphs

    Guangyao Zhai, Evin Pınar Örnek, Shun-Cheng Wu, Yan Di, Federico Tombari, Nassir Navab, Benjamin Busam

  32. Comparing Causal Frameworks: Potential Outcomes, Structural Models, Graphs, and Abstractions

    Duligur Ibeling, Thomas Icard

  33. Complex Query Answering on Eventuality Knowledge Graph with Implicit Logical Constraints

    Jiaxin Bai, Xin Liu, Weiqi Wang, Chen Luo, Yangqiu Song

  34. Curvature Filtrations for Graph Generative Model Evaluation

    Joshua Southern, Jeremy Wayland, Michael Bronstein, Bastian Rieck

  35. D4Explainer: In-distribution Explanations of Graph Neural Network via Discrete Denoising Diffusion

    Jialin Chen, Shirley Wu, Abhijit Gupta, Rex Ying

  36. DIFUSCO: Graph-based Diffusion Solvers for Combinatorial Optimization

    Zhiqing Sun, Yiming Yang

  37. Data-Centric Learning from Unlabeled Graphs with Diffusion Model

    Gang Liu, Eric Inae, Tong Zhao, Jiaxin Xu, Tengfei Luo, Meng Jiang

  38. Deciphering Spatio-Temporal Graph Forecasting: A Causal Lens and Treatment

    Yutong Xia, Yuxuan Liang, Haomin Wen, Xu Liu, Kun Wang, Zhengyang Zhou, Roger Zimmermann

  39. Deep Gaussian Markov Random Fields for Graph-Structured Dynamical Systems

    Fiona Lippert, Bart Kranstauber, Emiel van Loon, Patrick Forré

  40. Deep Insights into Noisy Pseudo Labeling on Graph Data

    Botao WANG, Jia Li, Yang Liu, Jiashun Cheng, Yu Rong, Wenjia Wang, Fugee Tsung

  41. Demystifying Oversmoothing in Attention-Based Graph Neural Networks

    Xinyi Wu, Amir Ajorlou, Zihui Wu, Ali Jadbabaie

  42. Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All?

    Haitao Mao, Zhikai Chen, Wei Jin, Haoyu Han, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang

  43. Differentiable Neuro-Symbolic Reasoning on Large-Scale Knowledge Graphs

    CHEN SHENGYUAN, Yunfeng Cai, Huang Fang, Xiao Huang, Mingming Sun

  44. Differentially Private Decoupled Graph Convolutions for Multigranular Topology Protection

    Eli Chien, Wei-Ning Chen, Chao Pan, Pan Li, Ayfer Ozgur, Olgica Milenkovic

  45. Diffusion Model for Graph Inverse Problems: Towards Effective Source Localization on Complex Networks

    Xin Yan, Qiang He, Hui Fang

  46. Directed Cyclic Graph for Causal Discovery from Multivariate Functional Data

    Saptarshi Roy, Raymond K. W. Wong, Yang Ni

  47. Directional Diffusion Model for Graph Representation Learning

    Run Yang, Yuling Yang, Fan Zhou, Qiang Sun

  48. Does Graph Distillation See Like Vision Dataset Counterpart?

    Beining Yang, Kai Wang, Qingyun Sun, Cheng Ji, Xingcheng Fu, Hao Tang, Yang You, Jianxin Li

  49. Does Invariant Graph Learning via Environment Augmentation Learn Invariance?

    Yongqiang Chen, Yatao Bian, Kaiwen Zhou, Binghui Xie, Bo Han, James Cheng

  50. Efficient Learning of Linear Graph Neural Networks via Node Subsampling

    Seiyun Shin, Ilan Shomorony, Han Zhao

  51. Enabling tabular deep learning when $d \gg n$ with an auxiliary knowledge graph

    Camilo Ruiz, Hongyu Ren, Kexin Huang, Jure Leskovec

  52. Environment-Aware Dynamic Graph Learning for Out-of-Distribution Generalization

    Haonan Yuan, Qingyun Sun, Xingcheng Fu, Ziwei Zhang, Cheng Ji, Hao Peng, Jianxin Li

  53. Equivariant Neural Operator Learning with Graphon Convolution

    Chaoran Cheng, Jian Peng

  54. Equivariant Spatio-Temporal Attentive Graph Networks to Simulate Physical Dynamics

    Liming Wu, Zhichao Hou, Jirui Yuan, Yu Rong, Wenbing Huang

  55. Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking

    Juanhui Li, Harry Shomer, Haitao Mao, Shenglai Zeng, Yao Ma, Neil Shah, Jiliang Tang, Dawei Yin

  56. Evaluating Post-hoc Explanations for Graph Neural Networks via Robustness Analysis

    Junfeng Fang, Wei Liu, Xiang Wang, Zemin Liu, An Zhang, Yuan Gao, Xiangnan He

  57. Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts

    Gleb Bazhenov, Denis Kuznedelev, Andrey Malinin, Artem Babenko, Liudmila Prokhorenkova

  58. Evaluating Self-Supervised Learning for Molecular Graph Embeddings

    Hanchen Wang, Jean Kaddour, Shengchao Liu, Jian Tang, Joan Lasenby, Qi Liu

  59. Facilitating Graph Neural Networks with Random Walk on Simplicial Complexes

    Cai Zhou, Xiyuan Wang, Muhan Zhang

  60. Fair Graph Distillation

    Qizhang Feng, Zhimeng Jiang, Ruiquan Li, Yicheng Wang, Na Zou, Jiang Bian, Xia Hu

  61. Fast Approximation of Similarity Graphs with Kernel Density Estimation

    Peter Macgregor, He Sun

  62. FedGCN: Convergence-Communication Tradeoffs in Federated Training of Graph Convolutional Networks

    Yuhang Yao, Weizhao Jin, Srivatsan Ravi, Carlee Joe-Wong

  63. Fine-grained Expressivity of Graph Neural Networks

    Jan Böker, Ron Levie, Ningyuan Huang, Soledad Villar, Christopher Morris

  64. FourierGNN: Rethinking Multivariate Time Series Forecasting from a Pure Graph Perspective

    Kun Yi, Qi Zhang, Wei Fan, Hui He, Liang Hu, Pengyang Wang, Ning An, Longbing Cao, Zhendong Niu

  65. Fragment-based Pretraining and Finetuning on Molecular Graphs

    Kha-Dinh Luong, Ambuj K Singh

  66. From Trainable Negative Depth to Edge Heterophily in Graphs

    Yuchen Yan, Yuzhong Chen, Huiyuan Chen, Minghua Xu, Mahashweta Das, Hao Yang, Hanghang Tong

  67. Front-door Adjustment Beyond Markov Equivalence with Limited Graph Knowledge

    Abhin Shah, Karthikeyan Shanmugam, Murat Kocaoglu

  68. Fused Gromov-Wasserstein Graph Mixup for Graph-level Classifications

    Xinyu Ma, Xu Chu, Yasha Wang, Yang Lin, Junfeng Zhao, Liantao Ma, Wenwu Zhu

  69. GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection

    Jianheng Tang, Fengrui Hua, Ziqi Gao, Peilin Zhao, Jia Li

  70. GALOPA: Graph Transport Learning with Optimal Plan Alignment

    Yejiang Wang, Yuhai Zhao, Daniel Zhengkui Wang, Ling Li

  71. GIMLET: A Unified Graph-Text Model for Instruction-Based Molecule Zero-Shot Learning

    Haiteng Zhao, Shengchao Liu, Ma Chang, Hannan Xu, Jie Fu, Zhihong Deng, Lingpeng Kong, Qi Liu

  72. GLEMOS: Benchmark for Instantaneous Graph Learning Model Selection

    Namyong Park, Ryan Rossi, Xing Wang, Antoine Simoulin, Nesreen K. Ahmed, Christos Faloutsos

  73. GNNEvaluator: Evaluating GNN Performance On Unseen Graphs Without Labels

    Xin Zheng, Miao Zhang, Chunyang Chen, Soheila Molaei, Chuan Zhou, Shirui Pan

  74. Generalised f-Mean Aggregation for Graph Neural Networks

    Ryan Kortvelesy, Steven D Morad, Amanda Prorok

  75. Generative Pre-Training of Spatio-Temporal Graph Neural Networks

    Zhonghang Li, Lianghao Xia, Yong Xu, Chao Huang

  76. Geometric Analysis of Matrix Sensing over Graphs

    Haixiang Zhang, Ying Chen, Javad Lavaei

  77. Graph Clustering with Graph Neural Networks

    Anton Tsitsulin, John Palowitch, Bryan Perozzi, Emmanuel Müller

  78. Graph Convolutional Kernel Machine versus Graph Convolutional Networks

    Zhihao Wu, Zhao Zhang, Jicong Fan

  79. Graph Denoising Diffusion for Inverse Protein Folding

    Kai Yi, Bingxin Zhou, Yiqing Shen, Pietro Lió, Yuguang Wang

  80. Graph Mixture of Experts: Learning on Large-Scale Graphs with Explicit Diversity Modeling

    Haotao Wang, Ziyu Jiang, Yuning You, Yan Han, Gaowen Liu, Jayanth Srinivasa, Ramana Kompella, Zhangyang "Atlas" Wang

  81. Graph Neural Networks for Road Safety Modeling: Datasets and Evaluations for Accident Analysis

    Abhinav Nippani, Dongyue Li, Haotian Ju, Haris Koutsopoulos, Hongyang Zhang

  82. Graph of Circuits with GNN for Exploring the Optimal Design Space

    Aditya Shahane, Saripilli Swapna Manjiri, Sandeep Kumar, Ankesh Jain

  83. Graph-Structured Gaussian Processes for Transferable Graph Learning

    Jun Wu, Lisa Ainsworth, Andrew Leakey, Haixun Wang, Jingrui He

  84. GraphACL: Simple Asymmetric Contrastive Learning of Graphs

    Teng Xiao, Huaisheng Zhu, Zhengyu Chen, Suhang Wang

  85. GraphAdapter: Tuning Vision-Language Models With Dual Knowledge Graph

    Xin Li, Dongze Lian, Zhihe Lu, Jiawang Bai, Zhibo Chen, Xinchao Wang

  86. GraphMP: Graph Neural Network-based Motion Planning with Efficient Graph Search

    Xiao Zang, Miao Yin, Jinqi Xiao, Saman Zonouz, Bo Yuan

  87. GraphPatcher: Mitigating Degree Bias for Graph Neural Networks via Test-time Node Patching

    Mingxuan Ju, Tong Zhao, Wenhao Yu, Neil Shah, Yanfang Ye

  88. Graphs Contrastive Learning with Stable and Scalable Spectral Encoding

    Deyu Bo, Yuan Fang, Yang Liu, Chuan Shi

  89. How to Turn Your Knowledge Graph Embeddings into Generative Models via Probabilistic Circuits

    Lorenzo Loconte, Nicola Di Mauro, Robert Peharz, Antonio Vergari

  90. HyTrel: Hypergraph-enhanced Tabular Data Representation Learning

    Pei Chen, Soumajyoti Sarkar, Leonard Lausen, Balasubramaniam Srinivasan, Sheng Zha, Ruihong Huang, George Karypis

  91. Imagine That! Abstract-to-Intricate Text-to-Image Synthesis with Scene Graph Hallucination Diffusion

    Shengqiong Wu, Hao Fei, Hanwang Zhang, Tat-Seng Chua

  92. Improving Graph Matching with Positional Reconstruction Encoder-Decoder Network

    Yixiao Zhou, Ruiqi Jia, Xiaoqing Lyu, Yumeng Zhao, Hefeng Quan, Hongxiang Lin

  93. Interpretable Graph Networks Formulate Universal Algebra Conjectures

    Francesco Giannini, Stefano Fioravanti, Oguzhan Keskin, Alisia Lupidi, Lucie Charlotte Magister, Pietro Lió, Pietro Barbiero

  94. Interpretable Prototype-based Graph Information Bottleneck

    Sangwoo Seo, Sungwon Kim, Chanyoung Park

  95. Intervention Generalization: A View from Factor Graph Models

    Gecia Bravo-Hermsdorff, David Watson, Jialin Yu, Jakob Zeitler, Ricardo Silva

  96. Joint Feature and Differentiable $ k $-NN Graph Learning using Dirichlet Energy

    Lei Xu, Lei Chen, Rong Wang, Feiping Nie, Xuelong Li

  97. Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization

    Shurui Gui, Meng Liu, Xiner Li, Youzhi Luo, Shuiwang Ji

  98. LD2: Scalable Heterophilous Graph Neural Network with Decoupled Embedding

    Ningyi Liao, Siqiang Luo, Xiang Li, Jieming Shi

  99. Language Semantic Graph Guided Data-Efficient Learning

    Wenxuan Ma, Shuang Li, lincan Cai, Jingxuan Kang

  100. Large sample spectral analysis of graph-based multi-manifold clustering

    Nicolas Garcia Trillos, Pengfei He, Chenghui Li

  101. Latent Graph Inference with Limited Supervision

    Jianglin Lu, Yi Xu, Huan Wang, Yue Bai, Yun Fu

  102. Learning Efficient Surrogate Dynamic Models with Graph Spline Networks

    Chuanbo Hua, Federico Berto, Michael Poli, Stefano Massaroli, Jinkyoo Park

  103. Learning Invariant Representations of Graph Neural Networks via Cluster Generalization

    Xiao Wang, Donglin Xia, Nian Liu, Chuan Shi

  104. Learning Large Graph Property Prediction via Graph Segment Training

    Kaidi Cao, Phitchaya Phothilimtha, Sami Abu-El-Haija, Dustin Zelle, Yanqi Zhou, Charith Mendis, Jure Leskovec, Bryan Perozzi

  105. Learning Latent Causal Graphs with Unknown Interventions

    Yibo Jiang, Bryon Aragam

  106. Learning Rule-Induced Subgraph Representations for Inductive Relation Prediction

    Tianyu Liu, Qitan Lv, Jie Wang, Shuling Yang, Hanzhu Chen

  107. Learning from Both Structural and Textual Knowledge for Inductive Knowledge Graph Completion

    Kunxun Qi, Jianfeng Du, Hai Wan

  108. Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNets

    Dinghuai Zhang, Hanjun Dai, Nikolay Malkin, Aaron Courville, Yoshua Bengio, Ling Pan

  109. Limits, approximation and size transferability for GNNs on sparse graphs via graphops

    Thien Le, Stefanie Jegelka

  110. LinGCN: Structural Linearized Graph Convolutional Network for Homomorphically Encrypted Inference

    Hongwu Peng, Ran Ran, Yukui Luo, Jiahui Zhao, Shaoyi Huang, Kiran Thorat, Tong Geng, Chenghong Wang, Xiaolin Xu, Wujie Wen, Caiwen Ding

  111. Live Graph Lab: Towards Open, Dynamic and Real Transaction Graphs with NFT

    Zhen Zhang, Bingqiao Luo, Shengliang Lu, Bingsheng He

  112. LogSpecT: Feasible Graph Learning Model from Stationary Signals with Recovery Guarantees

    Shangyuan LIU, Linglingzhi Zhu, Anthony Man-Cho So

  113. Lovász Principle for Unsupervised Graph Representation Learning

    Ziheng Sun, Chris Ding, Jicong Fan

  114. MAG-GNN: Reinforcement Learning Boosted Graph Neural Network

    Lecheng Kong, Jiarui Feng, Hao Liu, Dacheng Tao, Yixin Chen, Muhan Zhang

  115. MeGraph: Capturing Long-Range Interactions by Alternating Local and Hierarchical Aggregation on Multi-Scaled Graph Hierarchy

    Honghua Dong, Jiawei Xu, Yu Yang, Rui Zhao, Shiwen Wu, Chun Yuan, Xiu Li, Chris Maddison, Lei Han

  116. Mitigating the Popularity Bias in Graph-based Collaborative Filtering

    Yifei Zhang, Hao Zhu, yankai Chen, Zixing Song, Piotr Koniusz, Irwin King

  117. MuSe-GNN: Learning Unified Gene Representation From Multimodal Biological Graph Data

    Tianyu Liu, Yuge Wang, Rex Ying, Hongyu Zhao

  118. Multi-resolution Spectral Coherence for Graph Generation with Score-based Diffusion

    Hyuna Cho, Minjae Jeong, Sooyeon Jeon, Sungsoo Ahn, Won Hwa Kim

  119. Multi-task Graph Neural Architecture Search with Task-aware Collaboration and Curriculum

    Yijian Qin, Xin Wang, Ziwei Zhang, Hong Chen, Wenwu Zhu

  120. Network Regression with Graph Laplacians

    Yidong Zhou, Hans-Georg Müller

  121. Neural Graph Generation from Graph Statistics

    Kiarash Zahirnia, Oliver Schulte, Mark Coates, Yaochen Hu

  122. Neural Injective Functions for Multisets, Measures and Graphs via a Finite Witness Theorem

    Tal Amir, Steven Gortler, Ilai Avni, Ravina Ravina, Nadav Dym

  123. Neural Relation Graph: A Unified Framework for Identifying Label Noise and Outlier Data

    Jang-Hyun Kim, Sangdoo Yun, Hyun Oh Song

  124. NeuroGraph: Benchmarks for Graph Machine Learning in Brain Connectomics

    Anwar Said, Roza Bayrak, Tyler Derr, Mudassir Shabbir, Daniel Moyer, Catie Chang, Xenofon Koutsoukos

  125. Newton–Cotes Graph Neural Networks: On the Time Evolution of Dynamic Systems

    Lingbing Guo, Weiqing Wang, Zhuo Chen, Ningyu Zhang, Zequn Sun, Yixuan Lai, Qiang Zhang, Huajun Chen

  126. No Change, No Gain: Empowering Graph Neural Networks with Expected Model Change Maximization for Active Learning

    Zixing Song, Yifei Zhang, Irwin King

  127. On Class Distributions Induced by Nearest Neighbor Graphs for Node Classification of Tabular Data

    Federico Errica

  128. On Learning Necessary and Sufficient Causal Graphs

    Hengrui Cai, Yixin Wang, Michael Jordan, Rui Song

  129. On the Ability of Graph Neural Networks to Model Interactions Between Vertices

    Noam Razin, Tom Verbin, Nadav Cohen

  130. On the Minimax Regret for Online Learning with Feedback Graphs

    Khaled Eldowa, Emmanuel Esposito, Tom Cesari, Nicolò Cesa-Bianchi

  131. OpenGSL: A Comprehensive Benchmark for Graph Structure Learning

    Zhou Zhiyao, Sheng Zhou, Bochao Mao, Xuanyi Zhou, Jiawei Chen, Qiaoyu Tan, Daochen Zha, Can Wang, Yan Feng, Chun Chen

  132. Optimal Block-wise Asymmetric Graph Construction for Graph-based Semi-supervised Learning

    Zixing Song, Yifei Zhang, Irwin King

  133. Optimality of Message-Passing Architectures for Sparse Graphs

    Aseem Baranwal, Kimon Fountoulakis, Aukosh Jagannath

  134. Outlier-Robust Gromov Wasserstein for Graph Data

    Lemin Kong, Jiajin Li, Jianheng Tang, Anthony Man-Cho So

  135. PERFOGRAPH: A Numerical Aware Program Graph Representation for Performance Optimization and Program Analysis

    Ali TehraniJamsaz, Quazi Ishtiaque Mahmud, Le Chen, Nesreen K. Ahmed, Ali Jannesari

  136. PRODIGY: Enabling In-context Learning Over Graphs

    Qian Huang, Hongyu Ren, Peng Chen, Gregor Kržmanc, Daniel Zeng, Percy Liang, Jure Leskovec

  137. Partial Multi-Label Learning with Probabilistic Graphical Disambiguation

    Jun-Yi Hang, Min-Ling Zhang

  138. Penguin: Parallel-Packed Homomorphic Encryption for Fast Graph Convolutional Network Inference

    Ran Ran, Nuo Xu, Tao Liu, Wei Wang, Gang Quan, Wujie Wen

  139. PlanE: Representation Learning over Planar Graphs

    Radoslav Dimitrov, Zeyang Zhao, Ralph Abboud, Ismail Ceylan

  140. Practical Contextual Bandits with Feedback Graphs

    Mengxiao Zhang, Yuheng Zhang, Olga Vrousgou, Haipeng Luo, Paul Mineiro

  141. Predicting Global Label Relationship Matrix for Graph Neural Networks under Heterophily

    Langzhang Liang, Xiangjing Hu, Zenglin Xu, Zixing Song, Irwin King

  142. Private subgraph counting using alternatives to global sensitivity

    Dung Nguyen, Mahantesh Halappanavar, Venkatesh Srinivasan, Anil Vullikanti

  143. Provable Training for Graph Contrastive Learning

    Yue Yu, Xiao Wang, Mengmei Zhang, Nian Liu, Chuan Shi

  144. Re-Think and Re-Design Graph Neural Networks in Spaces of Continuous Graph Diffusion Functionals

    Tingting Dan, Jiaqi Ding, Ziquan Wei, Shahar Kovalsky, Minjeong Kim, Won Hwa Kim, Guorong Wu

  145. Recurrent Temporal Revision Graph Networks

    Yizhou Chen, Anxiang Zeng, Qingtao Yu, Kerui Zhang, Cao Yuanpeng, Kangle Wu, Guangda Huzhang, Han Yu, Zhiming Zhou

  146. Relational Curriculum Learning for Graph Neural Network

    Zheng Zhang, Junxiang Wang, Liang Zhao

  147. Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules

    ZHIYUAN LIU, Yaorui Shi, An Zhang, Enzhi Zhang, Kenji Kawaguchi, Xiang Wang, Tat-Seng Chua

  148. SPA: A Graph Spectral Alignment Perspective for Domain Adaptation

    Zhiqing Xiao, Haobo Wang, Ying Jin, Lei Feng, Gang Chen, Fei Huang, Junbo Zhao

  149. Self-supervised Graph Neural Networks via Low-Rank Decomposition

    Liang Yang, Runjie Shi, Qiuliang Zhang, bingxin niu, Zhen Wang, Chuan Wang, Xiaochun Cao

  150. Sheaf Hypergraph Networks

    Iulia Duta, Giulia Cassarà, Fabrizio Silvestri, Pietro Lió

  151. Simplifying and Empowering Transformers for Large-Graph Representations

    Qitian Wu, Wentao Zhao, Chenxiao Yang, Hengrui Zhang, Fan Nie, Haitian Jiang, Yatao Bian, Junchi Yan

  152. Sparse Graph Learning from Spatiotemporal Time Series

    Andrea Cini, Daniele Zambon, Cesare Alippi

  153. Spectral Invariant Learning for Dynamic Graphs under Distribution Shifts

    Zeyang Zhang, Xin Wang, Ziwei Zhang, Zhou Qin, Weigao Wen, Hui Xue', Haoyang Li, Wenwu Zhu

  154. Structure preserving reversible and irreversible bracket dynamics for deep graph neural networks

    Anthony Gruber, Kookjin Lee, Nathaniel Trask

  155. Structure-free Graph Condensation: From Large-scale Graphs to Condensed Graph-free Data

    Xin Zheng, Miao Zhang, Chunyang Chen, Quoc Viet Hung Nguyen, Xingquan Zhu, Shirui Pan

  156. SyncTREE: Fast Timing Analysis for Integrated Circuit Design through a Physics-informed Tree-based Graph Neural Network

    Yuting Hu, Jiajie Li, Florian Klemme, Gi-Joon Nam, Tengfei Ma, Hussam Amrouch, Jinjun Xiong

  157. TFLEX: Temporal Feature-Logic Embedding Framework for Complex Reasoning over Temporal Knowledge Graph

    Xueyuan Lin, Chengjin Xu, Haihong E, Fenglong Su, Gengxian Zhou, Tianyi Hu, Ningyuan Li, Mingzhi Sun, Haoran Luo

  158. Tailoring Self-Attention for Graph via Rooted Subtrees

    Siyuan Huang, Yunchong Song, Jiayue Zhou, Zhouhan Lin

  159. Taming Local Effects in Graph-based Spatiotemporal Forecasting

    Andrea Cini, Ivan Marisca, Daniele Zambon, Cesare Alippi

  160. TempME: Towards the Explainability of Temporal Graph Neural Networks via Motif Discovery

    Jialin Chen, Rex Ying

  161. Temporal Graph Benchmark for Machine Learning on Temporal Graphs

    Shenyang Huang, Farimah Poursafaei, Jacob Danovitch, Matthias Fey, Weihua Hu, Emanuele Rossi, Jure Leskovec, Michael Bronstein, Guillaume Rabusseau, Reihaneh Rabbany

  162. The Graphical Matrix Pencil Method: Exchangeable Distributions with Prescribed Subgraph Densities

    Lee Gunderson, Gecia Bravo-Hermsdorff, Peter Orbanz

  163. The expressive power of pooling in Graph Neural Networks

    Filippo Maria Bianchi, Veronica Lachi

  164. Towards Better Dynamic Graph Learning: New Architecture and Unified Library

    Le Yu, Leilei Sun, Bowen Du, Weifeng Lv

  165. Towards Label Position Bias in Graph Neural Networks

    Haoyu Han, Xiaorui Liu, Feng Shi, MohamadAli Torkamani, Charu Aggarwal, Jiliang Tang

  166. Towards Self-Interpretable Graph-Level Anomaly Detection

    Yixin Liu, Kaize Ding, Qinghua Lu, Fuyi Li, Leo Yu Zhang, Shirui Pan

  167. TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphs

    Phitchaya Phothilimtha, Sami Abu-El-Haija, Kaidi Cao, Bahare Fatemi, Charith Mendis, Bryan Perozzi

  168. Train Once and Explain Everywhere: Pre-training Interpretable Graph Neural Networks

    Jun Yin, Senzhang Wang, Hao Yan, Chaozhuo Li, Jianxun Lian

  169. Transformers over Directed Acyclic Graphs

    Yuankai Luo, Veronika Thost, Lei Shi

  170. Truncated Affinity Maximization for Graph Anomaly Detection

    Hezhe Qiao, Guansong Pang

  171. UUKG: Unified Urban Knowledge Graph Dataset for Urban Spatiotemporal Prediction

    Yansong Ning, Hao Liu, Hao Wang, Zhenyu Zeng, Hui Xiong

  172. Uncertainty Quantification over Graph with Conformalized Graph Neural Networks

    Kexin Huang, Ying Jin, Emmanuel Candes, Jure Leskovec

  173. Universal Prompt Tuning for Graph Neural Networks

    Taoran Fang, Yunchao Zhang, YANG YANG, Chunping Wang, Lei Chen

  174. Unleashing the Power of Graph Data Augmentation on Covariate Shift

    Yongduo Sui, Qitian Wu, Jiancan Wu, Qing Cui, Longfei Li, Jun Zhou, Xiang Wang, Xiangnan He

  175. Unsupervised Graph Neural Architecture Search with Disentangled Self-Supervision

    Zeyang Zhang, Xin Wang, Ziwei Zhang, Guangyao Shen, Shiqi Shen, Wenwu Zhu

  176. V-InFoR: A Robust Graph Neural Networks Explainer for Structurally Corrupted Graphs

    Jun Yin, Senzhang Wang, Chaozhuo Li, Xing Xie, Jianxin Wang

  177. Variational Annealing on Graphs for Combinatorial Optimization

    Sebastian Sanokowski, Wilhelm Berghammer, Sepp Hochreiter, Sebastian Lehner

  178. Video-Mined Task Graphs for Keystep Recognition in Instructional Videos

    Kumar Ashutosh, Santhosh Kumar Ramakrishnan, Triantafyllos Afouras, Kristen Grauman

  179. WalkLM: A Uniform Language Model Fine-tuning Framework for Attributed Graph Embedding

    Yanchao Tan, Zihao Zhou, Hang Lv, Weiming Liu, Carl Yang

  180. What functions can Graph Neural Networks compute on random graphs? The role of Positional Encoding

    Nicolas Keriven, Samuel Vaiter

  181. When Do Graph Neural Networks Help with Node Classification: Investigating the Homophily Principle on Node Distinguishability

    Sitao Luan, Chenqing Hua, Minkai Xu, Qincheng Lu, Jiaqi Zhu, Xiao-Wen Chang, Jie Fu, Jure Leskovec, Doina Precup

  182. Zero-One Laws of Graph Neural Networks

    Sam Adam-Day, Iliant, Ismail Ceylan

  183. [Re] $\mathcal{G}$-Mixup: Graph Data Augmentation for Graph Classification

    Ermin Omeragic, Vuk Đuranović

  184. [Re] On Explainability of Graph Neural Networks via Subgraph Explorations

    Yannik Mahlau, Lukas Berg, Leonie Kayser

  1. Knowledge Graphs for Knowing More and Knowing for Sure

    Steffen Staab

  2. Combining Inductive and Deductive Reasoning for Query Answering over Incomplete Knowledge Graphs

    Medina Andresel, Trung-Kien Tran, Csaba Domokos, Pasquale Minervini, Daria Stepanova

  3. GraphERT-- Transformers-based Temporal Dynamic Graph Embedding

    Moran Beladev, Gilad Katz, Lior Rokach, Uriel Singer, Kira Radinsky

  4. Faster Approximation Algorithms for Parameterized Graph Clustering and Edge Labeling

    Vedangi Bengali, Nate Veldt

  5. Bridged-GNN: Knowledge Bridge Learning for Effective Knowledge Transfer

    Wendong Bi, Xueqi Cheng, Bingbing Xu, Xiaoqian Sun, Li Xu, Huawei Shen

  6. How Expressive are Graph Neural Networks in Recommendation?

    Xuheng Cai, Lianghao Xia, Xubin Ren, Chao Huang

  7. Learning Pair-Centric Representation for Link Sign Prediction with Subgraph

    Jushuo Chen, Feifei Dai, Xiaoyan Gu, Haihui Fan, Jiang Zhou, Bo Li, Weiping Wang

  8. Can Knowledge Graphs Simplify Text?

    Anthony Colas, Haodi Ma, Xuanli He, Yang Bai, Daisy Zhe Wang

  9. Cross-heterogeneity Graph Few-shot Learning

    Pengfei Ding, Yan Wang, Guanfeng Liu

  10. Zero-shot Item-based Recommendation via Multi-task Product Knowledge Graph Pre-Training

    Ziwei Fan, Zhiwei Liu, Shelby Heinecke, Jianguo Zhang, Huan Wang, Caiming Xiong, Philip S. Yu

  11. Spatial-Temporal Graph Boosting Networks: Enhancing Spatial-Temporal Graph Neural Networks via Gradient Boosting

    Yujie Fan, Chin-Chia Michael Yeh, Huiyuan Chen, Yan Zheng, Liang Wang, Junpeng Wang, Xin Dai, Zhongfang Zhuang, Wei Zhang

  12. BOMGraph: Boosting Multi-scenario E-commerce Search with a Unified Graph Neural Network

    Shuai Fan, Jinping Gou, Yang Li, Jiaxing Bai, Chen Lin, Wanxian Guan, Xubin Li, Hongbo Deng, Jian Xu, Bo Zheng

  13. Cognitive-inspired Graph Redundancy Networks for Multi-source Information Fusion

    Yao Fu, Junhong Wan, Junlan Yu, Weihao Jiang, Shiliang Pu

  14. On the Trade-off between Over-smoothing and Over-squashing in Deep Graph Neural Networks

    Jhony H. Giraldo, Konstantinos Skianis, Thierry Bouwmans, Fragkiskos D. Malliaros

  15. Homophily-enhanced Structure Learning for Graph Clustering

    Ming Gu, Gaoming Yang, Sheng Zhou, Ning Ma, Jiawei Chen, Qiaoyu Tan, Meihan Liu, Jiajun Bu

  16. KG4Ex: An Explainable Knowledge Graph-Based Approach for Exercise Recommendation

    Quanlong Guan, Fang Xiao, Xinghe Cheng, Liangda Fang, Ziliang Chen, Guanliang Chen, Weiqi Luo

  17. Targeted Shilling Attacks on GNN-based Recommender Systems

    Sihan Guo, Ting Bai, Weihong Deng

  18. Interpretable Fake News Detection with Graph Evidence

    Hao Guo, Weixin Zeng, Jiuyang Tang, Xiang Zhao

  19. Towards Fair Graph Neural Networks via Graph Counterfactual

    Zhimeng Guo, Jialiang Li, Teng Xiao, Yao Ma, Suhang Wang

  20. Robust Basket Recommendation via Noise-tolerated Graph Contrastive Learning

    Xinrui He, Tianxin Wei, Jingrui He

  21. Celebrity-aware Graph Contrastive Learning Framework for Social Recommendation

    Zheng Hu, Satoshi Nakagawa, Liang Luo, Yu Gu, Fuji Ren

  22. HyperFormer: Enhancing Entity and Relation Interaction for Hyper-Relational Knowledge Graph Completion

    Zhiwei Hu, Víctor Gutiérrez-Basulto, Zhiliang Xiang, Ru Li, Jeff Z. Pan

  23. Enhanced Template-Free Reaction Prediction with Molecular Graphs and Sequence-based Data Augmentation

    Haozhe Hu, Yongquan Jiang, Yan Yang, Jim X. Chen

  24. Independent Distribution Regularization for Private Graph Embedding

    Qi Hu, Yangqiu Song

  25. Liberate Pseudo Labels from Over-Dependence: Label Information Migration on Sparsely Labeled Graphs

    Zhihui Hu, Yao Fu, Hong Zhao, Xiaoyu Cai, Weihao Jiang, Shiliang Pu

  26. Relevant Entity Selection: Knowledge Graph Bootstrapping via Zero-Shot Analogical Pruning

    Lucas Jarnac, Miguel Couceiro, Pierre Monnin

  27. Robust Graph Clustering via Meta Weighting for Noisy Graphs

    Hyeonsoo Jo, Fanchen Bu, Kijung Shin

  28. A Model-Agnostic Method to Interpret Link Prediction Evaluation of Knowledge Graph Embeddings

    Narayanan Asuri Krishnan, Carlos R. Rivero

  29. A Re-evaluation of Deep Learning Methods for Attributed Graph Clustering

    Xinying Lai, Dingming Wu, Christian S. Jensen, Kezhong Lu

  30. DuoGAT: Dual Time-oriented Graph Attention Networks for Accurate, Efficient and Explainable Anomaly Detection on Time-series

    Jongsoo Lee, Byeongtae Park, Dong-Kyu Chae

  31. GUARD: Graph Universal Adversarial Defense

    Jintang Li, Jie Liao, Ruofan Wu, Liang Chen, Zibin Zheng, Jiawang Dan, Changhua Meng, Weiqiang Wang

  32. ACGAN-GNNExplainer: Auxiliary Conditional Generative Explainer for Graph Neural Networks

    Yiqiao Li, Jianlong Zhou, Yifei Dong, Niusha Shafiabady, Fang Chen

  33. Heterogeneous Temporal Graph Neural Network Explainer

    Jiazheng Li, Chunhui Zhang, Chuxu Zhang

  34. Graph Enhanced Hierarchical Reinforcement Learning for Goal-oriented Learning Path Recommendation

    Qingyao Li, Wei Xia, Li'ang Yin, Jian Shen, Renting Rui, Weinan Zhang, Xianyu Chen, Ruiming Tang, Yong Yu

  35. Contrastive Representation Learning Based on Multiple Node-centered Subgraphs

    Dong Li, Wenjun Wang, Minglai Shao, Chen Zhao

  36. Multi-Order Relations Hyperbolic Fusion for Heterogeneous Graphs

    Junlin Li, Yueheng Sun, Minglai Shao

  37. THGNN: An Embedding-based Model for Anomaly Detection in Dynamic Heterogeneous Social Networks

    Yilin Li, Jiaqi Zhu, Congcong Zhang, Yi Yang, Jiawen Zhang, Ying Qiao, Hongan Wang

  38. Retrieving GNN Architecture for Collaborative Filtering

    Fengqi Liang, Huan Zhao, Zhenyi Wang, Wei Fang, Chuan Shi

  39. printf: Preference Modeling Based on User Reviews with Item Images and Textual Information via Graph Learning

    Hao-Lun Lin, Jyun-Yu Jiang, Ming-Hao Juan, Pu-Jen Cheng

  40. MATA: Combining Learnable Node Matching with A Algorithm for Approximate Graph Edit Distance Computation**

    Junfeng Liu, Min Zhou, Shuai Ma, Lujia Pan

  41. ForeSeer: Product Aspect Forecasting Using Temporal Graph Embedding

    Zixuan Liu, Gaurush Hiranandani, Kun Qian, Edward W. Huang, Yi Xu, Belinda Zeng, Karthik Subbian, Sheng Wang

  42. SMEF: Social-aware Multi-dimensional Edge Features-based Graph Representation Learning for Recommendation

    Xiao Liu, Shunmei Meng, Qianmu Li, Lianyong Qi, Xiaolong Xu, Wanchun Dou, Xuyun Zhang

  43. Self-Supervised Dynamic Hypergraph Recommendation based on Hyper-Relational Knowledge Graph

    Yi Liu, Hongrui Xuan, Bohan Li, Meng Wang, Tong Chen, Hongzhi Yin

  44. BRep-BERT: Pre-training Boundary Representation BERT with Sub-graph Node Contrastive Learning

    Yunzhong Lou, Xueyang Li, Haotian Chen, Xiangdong Zhou

  45. Timestamps as Prompts for Geography-Aware Location Recommendation

    Yan Luo, Haoyi Duan, Ye Liu, Fu-Lai Chung

  46. Improving Long-Tail Item Recommendation with Graph Augmentation

    Sichun Luo, Chen Ma, Yuanzhang Xiao, Linqi Song

  47. Multi-scale Graph Pooling Approach with Adaptive Key Subgraph for Graph Representations

    Yiqin Lv, Zhiliang Tian, Zheng Xie, Yiping Song

  48. A Graph Neural Network Model for Concept Prerequisite Relation Extraction

    Debjani Mazumder, Jiaul H. Paik, Anupam Basu

  49. Disparity, Inequality, and Accuracy Tradeoffs in Graph Neural Networks for Node Classification

    Arpit Merchant, Carlos Castillo

  50. Rule-based Knowledge Graph Completion with Canonical Models

    Simon Ott, Patrick Betz, Daria Stepanova, Mohamed H. Gad-Elrab, Christian Meilicke, Heiner Stuckenschmidt

  51. A Retrieve-and-Read Framework for Knowledge Graph Link Prediction

    Vardaan Pahuja, Boshi Wang, Hugo Latapie, Jayanth Srinivasa, Yu Su

  52. Bi-channel Multiple Sparse Graph Attention Networks for Session-based Recommendation

    Shutong Qiao, Wei Zhou, Junhao Wen, Hongyu Zhang, Min Gao

  53. ELTRA: An Embedding Method based on Learning-to-Rank to Preserve Asymmetric Information in Directed Graphs

    Masoud Rehyani Hamedani, Jin-Su Ryu, Sang-Wook Kim

  54. Dual-Process Graph Neural Network for Diversified Recommendation

    Yuanyi Ren, Hang Ni, Yingxue Zhang, Xi Wang, Guojie Song, Dong Li, Jianye Hao

  55. Incremental Graph Classification by Class Prototype Construction and Augmentation

    Yixin Ren, Li Ke, Dong Li, Hui Xue, Zhao Li, Shuigeng Zhou

  56. Seq-HyGAN: Sequence Classification via Hypergraph Attention Network

    Khaled Mohammed Saifuddin, Corey May, Farhan Tanvir, Muhammad Ifte Khairul Islam, Esra Akbas

  57. Transferable Structure-based Adversarial Attack of Heterogeneous Graph Neural Network

    Yu Shang, Yudong Zhang, Jiansheng Chen, Depeng Jin, Yong Li

  58. Improving Graph Domain Adaptation with Network Hierarchy

    Boshen Shi, Yongqing Wang, Fangda Guo, Jiangli Shao, Huawei Shen, Xueqi Cheng

  59. GiGaMAE: Generalizable Graph Masked Autoencoder via Collaborative Latent Space Reconstruction

    Yucheng Shi, Yushun Dong, Qiaoyu Tan, Jundong Li, Ninghao Liu

  60. Calibrate Graph Neural Networks under Out-of-Distribution Nodes via Deep Q-learning

    Weili Shi, Xueying Yang, Xujiang Zhao, Haifeng Chen, Zhiqiang Tao, Sheng Li

  61. Towards Fair Financial Services for All: A Temporal GNN Approach for Individual Fairness on Transaction Networks

    Zixing Song, Yuji Zhang, Irwin King

  62. Graph Inference via the Energy-efficient Dynamic Precision Matrix Estimation with One-bit Data

    Xiao Tan, Yangyang Shen, Meng Wang, Beilun Wang

  63. Explainable Spatio-Temporal Graph Neural Networks

    Jiabin Tang, Lianghao Xia, Chao Huang

  64. Citation Intent Classification and Its Supporting Evidence Extraction for Citation Graph Construction

    Hong-Jin Tsai, An-Zi Yen, Hen-Hsen Huang, Hsin-Hsi Chen

  65. Disentangled Interest importance aware Knowledge Graph Neural Network for Fund Recommendation

    Ke Tu, Wei Qu, Zhengwei Wu, Zhiqiang Zhang, Zhongyi Liu, Yiming Zhao, Le Wu, Jun Zhou, Guannan Zhang

  66. GraphFADE: Field-aware Decorrelation Neural Network for Graphs with Tabular Features

    Junhong Wan, Yao Fu, Junlan Yu, Weihao Jiang, Shiliang Pu, Ruiheng Yang

  67. UrbanFloodKG: An Urban Flood Knowledge Graph System for Risk Assessment

    Yu Wang, Feng Ye, Binquan Li, Gaoyang Jin, Dong Xu, Fengsheng Li

  68. Low-bit Quantization for Deep Graph Neural Networks with Smoothness-aware Message Propagation

    Shuang Wang, Bahaeddin Eravci, Rustam Guliyev, Hakan Ferhatosmanoglu

  69. Node-dependent Semantic Search over Heterogeneous Graph Neural Networks

    Zhenyi Wang, Huan Zhao, Fengqi Liang, Chuan Shi

  70. Dual Intents Graph Modeling for User-centric Group Discovery

    Xixi Wu, Yun Xiong, Yao Zhang, Yizhu Jiao, Jiawei Zhang

  71. SplitGNN: Spectral Graph Neural Network for Fraud Detection against Heterophily

    Bin Wu, Xinyu Yao, Boyan Zhang, Kuo-Ming Chao, Yinsheng Li

  72. DPGN: Denoising Periodic Graph Network for Life Service Recommendation

    Hao Xu, Huixuan Chi, Danyang Liu, Sheng Zhou, Mengdi Zhang

  73. A Bipartite Graph is All We Need for Enhancing Emotional Reasoning with Commonsense Knowledge

    Kailai Yang, Tianlin Zhang, Shaoxiong Ji, Sophia Ananiadou

  74. Group Identification via Transitional Hypergraph Convolution with Cross-view Self-supervised Learning

    Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu

  75. Causality-guided Graph Learning for Session-based Recommendation

    Dianer Yu, Qian Li, Hongzhi Yin, Guandong Xu

  76. MUSE: Multi-view Contrastive Learning for Heterophilic Graphs via Information Reconstruction

    Mengyi Yuan, Minjie Chen, Xiang Li

  77. AKE-GNN: Effective Graph Learning with Adaptive Knowledge Exchange

    Liang Zeng, Jin Xu, Zijun Yao, Yanqiao Zhu, Jian Li

  78. RDGSL: Dynamic Graph Representation Learning with Structure Learning

    Siwei Zhang, Yun Xiong, Yao Zhang, Yiheng Sun, Xi Chen, Yizhu Jiao, Yangyong Zhu

  79. iLoRE: Dynamic Graph Representation with Instant Long-term Modeling and Re-occurrence Preservation

    Siwei Zhang, Yun Xiong, Yao Zhang, Xixi Wu, Yiheng Sun, Jiawei Zhang

  80. Time-aware Graph Structure Learning via Sequence Prediction on Temporal Graphs

    Haozhen Zhang, Xueting Han, Xi Xiao, Jing Bai

  81. AspectMMKG: A Multi-modal Knowledge Graph with Aspect-aware Entities

    Jingdan Zhang, Jiaan Wang, Xiaodan Wang, Zhixu Li, Yanghua Xiao

  82. Efficient Exact Minimum k-Core Search in Real-World Graphs

    Qifan Zhang, Shengxin Liu

  83. HST-GT: Heterogeneous Spatial-Temporal Graph Transformer for Delivery Time Estimation in Warehouse-Distribution Integration E-Commerce

    Xiaohui Zhao, Shuai Wang, Hai Wang, Tian He, Desheng Zhang, Guang Wang

  84. Geometric Graph Learning for Protein Mutation Effect Prediction

    Kangfei Zhao, Yu Rong, Biaobin Jiang, Jianheng Tang, Hengtong Zhang, Jeffrey Xu Yu, Peilin Zhao

  85. Unveiling the Role of Message Passing in Dual-Privacy Preservation on GNNs

    Tianyi Zhao, Hui Hu, Lu Cheng

  86. Decentralized Graph Neural Network for Privacy-Preserving Recommendation

    Xiaolin Zheng, Zhongyu Wang, Chaochao Chen, Jiashu Qian, Yao Yang

  87. G-STO: Sequential Main Shopping Intention Detection via Graph-Regularized Stochastic Transformer

    Yuchen Zhuang, Xin Shen, Yan Zhao, Chaosheng Dong, Ming Wang, Jin Li, Chao Zhang

  88. HOVER: Homophilic Oversampling via Edge Removal for Class-Imbalanced Bot Detection on Graphs

    Bradley Ashmore, Lingwei Chen

  89. Non-Recursive Cluster-Scale Graph Interacted Model for Click-Through Rate Prediction

    Yuanchen Bei, Hao Chen, Shengyuan Chen, Xiao Huang, Sheng Zhou, Feiran Huang

  90. Counterfactual Graph Augmentation for Consumer Unfairness Mitigation in Recommender Systems

    Ludovico Boratto, Francesco Fabbri, Gianni Fenu, Mirko Marras, Giacomo Medda

  91. Self-supervised Learning and Graph Classification under Heterophily

    Yilin Ding, Zhen Liu, Hao Hao

  92. Geometric Matrix Completion via Sylvester Multi-Graph Neural Network

    Boxin Du, Changhe Yuan, Fei Wang, Hanghang Tong

  93. KGPR: Knowledge Graph Enhanced Passage Ranking

    Jinyuan Fang, Zaiqiao Meng, Craig Macdonald

  94. Neighborhood Homophily-based Graph Convolutional Network

    Shengbo Gong, Jiajun Zhou, Chenxuan Xie, Qi Xuan

  95. KGrEaT: A Framework to Evaluate Knowledge Graphs via Downstream Tasks

    Nicolas Heist, Sven Hertling, Heiko Paulheim

  96. Stochastic Subgraph Neighborhood Pooling for Subgraph Classification

    Shweta Ann Jacob, Paul Louis, Amirali Salehi-Abari

  97. S-Mixup: Structural Mixup for Graph Neural Networks

    Junghurn Kim, Sukwon Yun, Chanyoung Park

  98. Class Label-aware Graph Anomaly Detection

    Junghoon Kim, Yeonjun In, Kanghoon Yoon, Junmo Lee, Chanyoung Park

  99. Exploring Cohesive Subgraphs in Hypergraphs: The (k,g)-core Approach

    Dahee Kim, Junghoon Kim, Sungsu Lim, Hyun Ji Jeong

  100. Towards Trustworthy Rumor Detection with Interpretable Graph Structural Learning

    Leyuan Liu, Junyi Chen, Zhangtao Cheng, Wenxin Tai, Fan Zhou

  101. Boosting Meta-Learning Cold-Start Recommendation with Graph Neural Network

    Han Liu, Hongxiang Lin, Xiaotong Zhang, Fenglong Ma, Hongyang Chen, Lei Wang, Hong Yu, Xianchao Zhang

  102. STGIN: Spatial-Temporal Graph Interaction Network for Large-scale POI Recommendation

    Shaohua Liu, Yu Qi, Gen Li, Mingjian Chen, Teng Zhang, Jia Cheng, Jun Lei

  103. FairGraph: Automated Graph Debiasing with Gradient Matching

    Yezi Liu

  104. DCGNN: Dual-Channel Graph Neural Network for Social Bot Detection

    Nuoyan Lyu, Bingbing Xu, Fangda Guo, Huawei Shen

  105. Metapath-Guided Data-Augmentation For Knowledge Graphs

    Saurav Manchanda

  106. Learning Visibility Attention Graph Representation for Time Series Forecasting

    Shengzhong Mao, Xiao-Jun Zeng

  107. Graph Contrastive Learning with Graph Info-Min

    En Meng, Yong Liu

  108. Generative Graph Augmentation for Minority Class in Fraud Detection

    Lin Meng, Hesham Mostafa, Marcel Nassar, Xiaonan Zhang, Jiawei Zhang

  109. Efficient Differencing of System-level Provenance Graphs

    Yuta Nakamura, Iyad Kanj, Tanu Malik

  110. VN-Solver: Vision-based Neural Solver for Combinatorial Optimization over Graphs

    Mina Samizadeh, Guangmo Tong

  111. Network Embedding with Adaptive Multi-hop Contrast

    Chenhao Wang, Yong Liu, Yan Yang

  112. Training Heterogeneous Graph Neural Networks using Bandit Sampling

    Ta-Yang Wang, Rajgopal Kannan, Viktor Prasanna

  113. Adaptive Graph Neural Diffusion for Traffic Demand Forecasting

    Yiling Wu, Xinfeng Zhang, Yaowei Wang

  114. Geometry Interaction Augmented Graph Collaborative Filtering

    Jie Xu, Chaozhuo Li

  115. Mitigating Semantic Confusion from Hostile Neighborhood for Graph Active Learning

    Tianmeng Yang, Min Zhou, Yujing Wang, Zhengjie Lin, Lujia Pan, Bin Cui, Yunhai Tong

  116. Positive-Unlabeled Node Classification with Structure-aware Graph Learning

    Hansi Yang, Yongqi Zhang, Quanming Yao, James Kwok

  117. Graph-based Alignment and Uniformity for Recommendation

    Liangwei Yang, Zhiwei Liu, Chen Wang, Mingdai Yang, Xiaolong Liu, Jing Ma, Philip S. Yu

  118. BI-GCN: Bilateral Interactive Graph Convolutional Network for Recommendation

    Yinan Zhang, Pei Wang, Congcong Liu, Xiwei Zhao, Hao Qi, Jie He, Junsheng Jin, Changping Peng, Zhangang Lin, Jingping Shao

  119. Knowledge Graph Error Detection with Hierarchical Path Structure

    Zhao Zhang, Fuwei Zhang, Fuzhen Zhuang, Yongjun Xu

  120. Weight Matters: An Empirical Investigation of Distance Oracles on Knowledge Graphs

    Ke Zhang, Jiageng Chen, Zixian Huang, Gong Cheng

  121. LEAD-ID: Language-Enhanced Denoising and Intent Distinguishing Graph Neural Network for Sponsored Search Broad Retrievals

    Xiao Zhou, Ran Wang, Haorui Li, Qiang Liu, Xingxing Wang, Dong Wang

  122. CallMine: Fraud Detection and Visualization of Million-Scale Call Graphs

    Mirela Cazzolato, Saranya Vijayakumar, Meng-Chieh Lee, Catalina Vajiac, Namyong Park, Pedro Fidalgo, Agma J.M. Traina, Christos Faloutsos

  123. Enhancing Catalog Relationship Problems with Heterogeneous Graphs and Graph Neural Networks Distillation

    Boxin Du, Rob Barton, Grant Galloway, Junzhou Huang, Shioulin Sam, Ismail Tutar, Changhe Yuan

  124. FAF: A Risk Detection Framework on Industry-Scale Graphs

    Yice Luo, Guannan Wang, Yongchao Liu, Jiaxin Yue, Weihong Cheng, Binjie Fei

  125. Graph Learning for Exploratory Query Suggestions in an Instant Search System

    Enrico Palumbo, Andreas Damianou, Alice Wang, Alva Liu, Ghazal Fazelnia, Francesco Fabbri, Rui Ferreira, Fabrizio Silvestri, Hugues Bouchard, Claudia Hauff, Mounia Lalmas, Ben Carterette, Praveen Chandar, David Nyhan

  126. GBTTE: Graph Attention Network Based Bus Travel Time Estimation

    Yuecheng Rong, Juntao Yao, Jun Liu, Yifan Fang, Wei Luo, Hao Liu, Jie Ma, Zepeng Dan, Jinzhu Lin, Zhi Wu, Yan Zhang, Chuanming Zhang

  127. GraphFC: Customs Fraud Detection with Label Scarcity

    Karandeep Singh, Yu-Che Tsai, Cheng-Te Li, Meeyoung Cha, Shou-De Lin

  128. Voucher Abuse Detection with Prompt-based Fine-tuning on Graph Neural Networks

    Zhihao Wen, Yuan Fang, Yihan Liu, Yang Guo, Shuji Hao

  129. Logistics Audience Expansion via Temporal Knowledge Graph

    Hua Yan, Yingqiang Ge, Haotian Wang, Desheng Zhang, Yu Yang

  130. Graph Exploration Matters: Improving both Individual-Level and System-Level Diversity in WeChat Feed Recommendation

    Shuai Yang, Lixin Zhang, Feng Xia, Leyu Lin

  131. Multi-gate Mixture-of-Contrastive-Experts with Graph-based Gating Mechanism for TV Recommendation

    Cong Zhang, Dongyang Liu, Lin Zuo, Junlan Feng, Chao Deng, Jian Sun, Haitao Zeng, Yaohong Zhao

  132. Dual Interests-Aligned Graph Auto-Encoders for Cross-domain Recommendation in WeChat

    Jiawei Zheng, Hao Gu, Chonggang Song, Dandan Lin, Lingling Yi, Chuan Chen

  133. The µ-RA System for Recursive Path Queries over Graphs

    Amela Fejza, Pierre Genevès, Nabil Layaïda, Sarah Chlyah

  134. Investigating Natural and Artificial Dynamics in Graph Data Mining and Machine Learning

    Dongqi Fu

  135. A Neuro-symbolic Approach to Enhance Interpretability of Graph Neural Network through the Integration of External Knowledge

    Kislay Raj

  136. Exploiting Homeostatic Synaptic Modulation in Spiking Neural Networks for Semi-Supervised Graph Learning

    Mingkun Xu

  137. Leveraging Graph Neural Networks for User Profiling: Recent Advances and Open Challenges

    Erasmo Purificato, Ludovico Boratto, Ernesto William De Luca

  138. Reasoning beyond Triples: Recent Advances in Knowledge Graph Embeddings

    Bo Xiong, Mojtaba Nayyeri, Daniel Daza, Michael Cochez

  139. From User Activity Traces to Navigation Graph for Software Enhancement: An Application of Graph Neural Network (GNN) on a Real-World Non-Attributed Graph

    Ikram Boukharouba, Florence Sèdes, Christophe Bortolaso, Florent Mouysset

  140. Astrolabe: Visual Graph Database Queries with Tabular Output

    Michael Miller

  141. Workshop on Enterprise Knowledge Graphs using Large Language Models

    Rajeev Gupta, Srinath Srinivasa

  142. PGB: A PubMed Graph Benchmark for Heterogeneous Network Representation Learning

    Eric W. Lee, Joyce C. Ho

  143. Datasets and Interfaces for Benchmarking Heterogeneous Graph Neural Networks

    Yijian Liu, Hongyi Zhang, Cheng Yang, Ao Li, Yugang Ji, Luhao Zhang, Tao Li, Jinyu Yang, Tianyu Zhao, Juan Yang, Hai Huang, Chuan Shi

  144. OpenGDA: Graph Domain Adaptation Benchmark for Cross-network Learning

    Boshen Shi, Yongqing Wang, Fangda Guo, Jiangli Shao, Huawei Shen, Xueqi Cheng

  1. Self-Supervised Graph Learning for Long-Tailed Cognitive Diagnosis

    Shanshan Wang, Zhen Zeng, Xun Yang, Xingyi Zhang

  2. Exposing the Self-Supervised Space-Time Correspondence Learning via Graph Kernels

    Zheyun Qin, Xiankai Lu, Xiushan Nie, Yilong Yin, Jianbing Shen

  3. Asynchronous Event Processing with Local-Shift Graph Convolutional Network

    Linhui Sun, Yifan Zhang, Jian Cheng, Hanqing Lu

  4. Multi-Modal Knowledge Hypergraph for Diverse Image Retrieval

    Yawen Zeng, Qin Jin, Tengfei Bao, Wenfeng Li

  5. MulGT: Multi-Task Graph-Transformer with Task-Aware Knowledge Injection and Domain Knowledge-Driven Pooling for Whole Slide Image Analysis

    Weiqin Zhao, Shujun Wang, Maximus Yeung, Tianye Niu, Lequan Yu

  6. Separate but Equal: Equality in Belief Propagation for Single Cycle Graphs

    Erel Cohen, Omer Lev, Roie Zivan

  7. Enhanced Multi-Relationships Integration Graph Convolutional Network for Inferring Substitutable and Complementary Items

    Huajie Chen, Jiyuan He, Weisheng Xu, Tao Feng, Ming Liu, Tianyu Song, Runfeng Yao, Yuanyuan Qiao

  8. Entity-Agnostic Representation Learning for Parameter-Efficient Knowledge Graph Embedding

    Mingyang Chen, Wen Zhang, Zhen Yao, Yushan Zhu, Yang Gao, Jeff Z. Pan, Huajun Chen

  9. Dual Low-Rank Graph Autoencoder for Semantic and Topological Networks

    Zhaoliang Chen, Zhihao Wu, Shiping Wang, Wenzhong Guo

  10. Learning Representations of Bi-level Knowledge Graphs for Reasoning beyond Link Prediction

    Chanyoung Chung, Joyce Jiyoung Whang

  11. Lifelong Embedding Learning and Transfer for Growing Knowledge Graphs

    Yuanning Cui, Yuxin Wang, Zequn Sun, Wenqiang Liu, Yiqiao Jiang, Kexin Han, Wei Hu

  12. DropMessage: Unifying Random Dropping for Graph Neural Networks

    Taoran Fang, Zhiqing Xiao, Chunping Wang, Jiarong Xu, Xuan Yang, Yang Yang

  13. MA-GCL: Model Augmentation Tricks for Graph Contrastive Learning

    Xumeng Gong, Cheng Yang, Chuan Shi

  14. Generic and Dynamic Graph Representation Learning for Crowd Flow Modeling

    Liangzhe Han, Ruixing Zhang, Leilei Sun, Bowen Du, Yanjie Fu, Tongyu Zhu

  15. Conditional Diffusion Based on Discrete Graph Structures for Molecular Graph Generation

    Han Huang, Leilei Sun, Bowen Du, Weifeng Lv

  16. T2-GNN: Graph Neural Networks for Graphs with Incomplete Features and Structure via Teacher-Student Distillation

    Cuiying Huo, Di Jin, Yawen Li, Dongxiao He, Yu-Bin Yang, Lingfei Wu

  17. Let Graph Be the Go Board: Gradient-Free Node Injection Attack for Graph Neural Networks via Reinforcement Learning

    Mingxuan Ju, Yujie Fan, Chuxu Zhang, Yanfang Ye

  18. GLCC: A General Framework for Graph-Level Clustering

    Wei Ju, Yiyang Gu, Binqi Chen, Gongbo Sun, Yifang Qin, Xingyuming Liu, Xiao Luo, Ming Zhang

  19. Signed Laplacian Graph Neural Networks

    Yu Li, Meng Qu, Jian Tang, Yi Chang

  20. Scalable and Effective Conductance-Based Graph Clustering

    Longlong Lin, Ronghua Li, Tao Jia

  21. Multi-Domain Generalized Graph Meta Learning

    Mingkai Lin, Wenzhong Li, Ding Li, Yizhou Chen, Guohao Li, Sanglu Lu

  22. IterDE: An Iterative Knowledge Distillation Framework for Knowledge Graph Embeddings

    Jiajun Liu, Peng Wang, Ziyu Shang, Chenxiao Wu

  23. Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating

    Yixin Liu, Yizhen Zheng, Daokun Zhang, Vincent CS Lee, Shirui Pan

  24. On Generalized Degree Fairness in Graph Neural Networks

    Zemin Liu, Trung-Kien Nguyen, Yuan Fang

  25. Graph Structure Learning on User Mobility Data for Social Relationship Inference

    Guangming Qin, Lexue Song, Yanwei Yu, Chao Huang, Wenzhe Jia, Yuan Cao, Junyu Dong

  26. Self-Supervised Continual Graph Learning in Adaptive Riemannian Spaces

    Li Sun, Junda Ye, Hao Peng, Feiyang Wang, Philip S. Yu

  27. Self-Organization Preserved Graph Structure Learning with Principle of Relevant Information

    Qingyun Sun, Jianxin Li, Beining Yang, Xingcheng Fu, Hao Peng, Philip S. Yu

  28. Easy Begun Is Half Done: Spatial-Temporal Graph Modeling with ST-Curriculum Dropout

    Hongjun Wang, Jiyuan Chen, Tong Pan, Zipei Fan, Xuan Song, Renhe Jiang, Lingyu Zhang, Yi Xie, Zhongyi Wang, Boyuan Zhang

  29. Cross-Domain Graph Anomaly Detection via Anomaly-Aware Contrastive Alignment

    Qizhou Wang, Guansong Pang, Mahsa Salehi, Wray Buntine, Christopher Leckie

  30. Beyond Graph Convolutional Network: An Interpretable Regularizer-Centered Optimization Framework

    Shiping Wang, Zhihao Wu, Yuhong Chen, Yong Chen

  31. Augmenting Affective Dependency Graph via Iterative Incongruity Graph Learning for Sarcasm Detection

    Xiaobao Wang, Yiqi Dong, Di Jin, Yawen Li, Longbiao Wang, Jianwu Dang

  32. Temporal Knowledge Graph Reasoning with Historical Contrastive Learning

    Yi Xu, Junjie Ou, Hui Xu, Luoyi Fu

  33. Next POI Recommendation with Dynamic Graph and Explicit Dependency

    Feiyu Yin, Yong Liu, Zhiqi Shen, Lisi Chen, Shuo Shang, Peng Han

  34. Learning to Count Isomorphisms with Graph Neural Networks

    Xingtong Yu, Zemin Liu, Yuan Fang, Xinming Zhang

  35. Cross-Domain Few-Shot Graph Classification with a Reinforced Task Coordinator

    Qiannan Zhang, Shichao Pei, Qiang Yang, Chuxu Zhang, Nitesh V. Chawla, Xiangliang Zhang

  36. Deep Graph Structural Infomax

    Wenting Zhao, Gongping Xu, Zhen Cui, Siqiang Luo, Cheng Long, Tong Zhang

  37. A Provable Framework of Learning Graph Embeddings via Summarization

    Houquan Zhou, Shenghua Liu, Danai Koutra, Huawei Shen, Xueqi Cheng

  38. GraphSR: A Data Augmentation Algorithm for Imbalanced Node Classification

    Mengting Zhou, Zhiguo Gong

  39. GRLSTM: Trajectory Similarity Computation with Graph-Based Residual LSTM

    Silin Zhou, Jing Li, Hao Wang, Shuo Shang, Peng Han

  40. Heterogeneous Graph Learning for Multi-Modal Medical Data Analysis

    Sein Kim, Namkyeong Lee, Junseok Lee, Dongmin Hyun, Chanyoung Park

  41. GRIP: Graph Representation of Immune Repertoire Using Graph Neural Network and Transformer

    Yongju Lee, Hyunho Lee, Kyoungseob Shin, Sunghoon Kwon

  42. Molformer: Motif-Based Transformer on 3D Heterogeneous Molecular Graphs

    Fang Wu, Dragomir Radev, Stan Z. Li

  43. Multi-Relational Contrastive Learning Graph Neural Network for Drug-Drug Interaction Event Prediction

    Zhankun Xiong, Shichao Liu, Feng Huang, Ziyan Wang, Xuan Liu, Zhongfei Zhang, Wen Zhang

  44. Scalable Edge Blocking Algorithms for Defending Active Directory Style Attack Graphs

    Mingyu Guo, Max Ward, Aneta Neumann, Frank Neumann, Hung Nguyen

  45. DHGE: Dual-View Hyper-Relational Knowledge Graph Embedding for Link Prediction and Entity Typing

    Haoran Luo, Haihong E, Ling Tan, Gengxian Zhou, Tianyu Yao, Kaiyang Wan

  46. Generalizing Downsampling from Regular Data to Graphs

    Davide Bacciu, Alessio Conte, Francesco Landolfi

  47. Learnable Spectral Wavelets on Dynamic Graphs to Capture Global Interactions

    Anson Bastos, Abhishek Nadgeri, Kuldeep Singh, Toyotaro Suzumura, Manish Singh

  48. FTM: A Frame-Level Timeline Modeling Method for Temporal Graph Representation Learning

    Bowen Cao, Qichen Ye, Weiyuan Xu, Yuexian Zou

  49. Where Will Players Move Next? Dynamic Graphs and Hierarchical Fusion for Movement Forecasting in Badminton

    Kai-Shiang Chang, Wei-Yao Wang, Wen-Chih Peng

  50. Graph Ordering Attention Networks

    Michail Chatzianastasis, Johannes Lutzeyer, George Dasoulas, Michalis Vazirgiannis

  51. Attribute and Structure Preserving Graph Contrastive Learning

    Jialu Chen, Gang Kou

  52. Context-Aware Safe Medication Recommendations with Molecular Graph and DDI Graph Embedding

    Qianyu Chen, Xin Li, Kunnan Geng, Mingzhong Wang

  53. Topological Pooling on Graphs

    Yuzhou Chen, Yulia R. Gel

  54. Wiener Graph Deconvolutional Network Improves Graph Self-Supervised Learning

    Jiashun Cheng, Man Li, Jia Li, Fugee Tsung

  55. Scalable Spatiotemporal Graph Neural Networks

    Andrea Cini, Ivan Marisca, Filippo Maria Bianchi, Cesare Alippi

  56. CrysGNN: Distilling Pre-trained Knowledge to Enhance Property Prediction for Crystalline Materials

    Kishalay Das, Bidisha Samanta, Pawan Goyal, Seung-Cheol Lee, Satadeep Bhattacharjee, Niloy Ganguly

  57. Eliciting Structural and Semantic Global Knowledge in Unsupervised Graph Contrastive Learning

    Kaize Ding, Yancheng Wang, Yingzhen Yang, Huan Liu

  58. Interpreting Unfairness in Graph Neural Networks via Training Node Attribution

    Yushun Dong, Song Wang, Jing Ma, Ninghao Liu, Jundong Li

  59. Graph Anomaly Detection via Multi-Scale Contrastive Learning Networks with Augmented View

    Jingcan Duan, Siwei Wang, Pei Zhang, En Zhu, Jingtao Hu, Hu Jin, Yue Liu, Zhibin Dong

  60. Directed Acyclic Graph Structure Learning from Dynamic Graphs

    Shaohua Fan, Shuyang Zhang, Xiao Wang, Chuan Shi

  61. Wasserstein Graph Distance Based on L1–Approximated Tree Edit Distance between Weisfeiler–Lehman Subtrees

    Zhongxi Fang, Jianming Huang, Xun Su, Hiroyuki Kasai

  62. Scalable Attributed-Graph Subspace Clustering

    Chakib Fettal, Lazhar Labiod, Mohamed Nadif

  63. Handling Missing Data via Max-Entropy Regularized Graph Autoencoder

    Ziqi Gao, Yifan Niu, Jiashun Cheng, Jianheng Tang, Lanqing Li, Tingyang Xu, Peilin Zhao, Fugee Tsung, Jia Li

  64. Interpolating Graph Pair to Regularize Graph Classification

    Hongyu Guo, Yongyi Mao

  65. Graph Knows Unknowns: Reformulate Zero-Shot Learning as Sample-Level Graph Recognition

    Jingcai Guo, Song Guo, Qihua Zhou, Ziming Liu, Xiaocheng Lu, Fushuo Huo

  66. Self-Supervised Bidirectional Learning for Graph Matching

    Wenqi Guo, Lin Zhang, Shikui Tu, Lei Xu

  67. Boosting Graph Neural Networks via Adaptive Knowledge Distillation

    Zhichun Guo, Chunhui Zhang, Yujie Fan, Yijun Tian, Chuxu Zhang, Nitesh V. Chawla

  68. Self-Supervised Learning for Anomalous Channel Detection in EEG Graphs: Application to Seizure Analysis

    Thi Kieu Khanh Ho, Narges Armanfard

  69. Self-Supervised Graph Attention Networks for Deep Weighted Multi-View Clustering

    Zongmo Huang, Yazhou Ren, Xiaorong Pu, Shudong Huang, Zenglin Xu, Lifang He

  70. Multi-View MOOC Quality Evaluation via Information-Aware Graph Representation Learning

    Lu Jiang, Yibin Wang, Jianan Wang, Pengyang Wang, Minghao Yin

  71. Spatio-Temporal Meta-Graph Learning for Traffic Forecasting

    Renhe Jiang, Zhaonan Wang, Jiawei Yong, Puneet Jeph, Quanjun Chen, Yasumasa Kobayashi, Xuan Song, Shintaro Fukushima, Toyotaro Suzumura

  72. Energy-Motivated Equivariant Pretraining for 3D Molecular Graphs

    Rui Jiao, Jiaqi Han, Wenbing Huang, Yu Rong, Yang Liu

  73. Local-Global Defense against Unsupervised Adversarial Attacks on Graphs

    Di Jin, Bingdao Feng, Siqi Guo, Xiaobao Wang, Jianguo Wei, Zhen Wang

  74. Grouping Matrix Based Graph Pooling with Adaptive Number of Clusters

    Sung Moon Ko, Sungjun Cho, Dae-Woong Jeong, Sehui Han, Moontae Lee, Honglak Lee

  75. LoNe Sampler: Graph Node Embeddings by Coordinated Local Neighborhood Sampling

    Konstantin Kutzkov

  76. I’m Me, We’re Us, and I’m Us: Tri-directional Contrastive Learning on Hypergraphs

    Dongjin Lee, Kijung Shin

  77. Time-Aware Random Walk Diffusion to Improve Dynamic Graph Learning

    Jong-whi Lee, Jinhong Jung

  78. Differentiable Meta Multigraph Search with Partial Message Propagation on Heterogeneous Information Networks

    Chao Li, Hao Xu, Kun He

  79. Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks

    Jintang Li, Zhouxin Yu, Zulun Zhu, Liang Chen, Qi Yu, Zibin Zheng, Sheng Tian, Ruofan Wu, Changhua Meng

  80. Restructuring Graph for Higher Homophily via Adaptive Spectral Clustering

    Shouheng Li, Dongwoo Kim, Qing Wang

  81. Towards Fine-Grained Explainability for Heterogeneous Graph Neural Network

    Tong Li, Jiale Deng, Yanyan Shen, Luyu Qiu, Huang Yongxiang, Caleb Chen Cao

  82. Dual Label-Guided Graph Refinement for Multi-View Graph Clustering

    Yawen Ling, Jianpeng Chen, Yazhou Ren, Xiaorong Pu, Jie Xu, Xiaofeng Zhu, Lifang He

  83. Hard Sample Aware Network for Contrastive Deep Graph Clustering

    Yue Liu, Xihong Yang, Sihang Zhou, Xinwang Liu, Zhen Wang, Ke Liang, Wenxuan Tu, Liang Li, Jingcan Duan, Cancan Chen

  84. Recovering the Graph Underlying Networked Dynamical Systems under Partial Observability: A Deep Learning Approach

    Sérgio Machado, Anirudh Sridhar, Paulo Gil, Jorge Henriques, José M. F. Moura, Augusto Santos

  85. Boundary Graph Neural Networks for 3D Simulations

    Andreas Mayr, Sebastian Lehner, Arno Mayrhofer, Christoph Kloss, Sepp Hochreiter, Johannes Brandstetter

  86. Multiplex Graph Representation Learning via Common and Private Information Mining

    Yujie Mo, Zongqian Wu, Yuhuan Chen, Xiaoshuang Shi, Heng Tao Shen, Xiaofeng Zhu

  87. Inferring Patient Zero on Temporal Networks via Graph Neural Networks

    Xiaolei Ru, Jack Murdoch Moore, Xin-Ya Zhang, Yeting Zeng, Gang Yan

  88. Neighbor Contrastive Learning on Learnable Graph Augmentation

    Xiao Shen, Dewang Sun, Shirui Pan, Xi Zhou, Laurence T. Yang

  89. Federated Learning on Non-IID Graphs via Structural Knowledge Sharing

    Yue Tan, Yixin Liu, Guodong Long, Jing Jiang, Qinghua Lu, Chengqi Zhang

  90. Metric Multi-View Graph Clustering

    Yuze Tan, Yixi Liu, Hongjie Wu, Jiancheng Lv, Shudong Huang

  91. Heterogeneous Graph Masked Autoencoders

    Yijun Tian, Kaiwen Dong, Chunhui Zhang, Chuxu Zhang, Nitesh V. Chawla

  92. USER: Unsupervised Structural Entropy-Based Robust Graph Neural Network

    Yifei Wang, Yupan Wang, Zeyu Zhang, Song Yang, Kaiqi Zhao, Jiamou Liu

  93. FedGS: Federated Graph-Based Sampling with Arbitrary Client Availability

    Zheng Wang, Xiaoliang Fan, Jianzhong Qi, Haibing Jin, Peizhen Yang, Siqi Shen, Cheng Wang

  94. Non-IID Transfer Learning on Graphs

    Jun Wu, Jingrui He, Elizabeth Ainsworth

  95. Extracting Low-/High- Frequency Knowledge from Graph Neural Networks and Injecting It into MLPs: An Effective GNN-to-MLP Distillation Framework

    Lirong Wu, Haitao Lin, Yufei Huang, Tianyu Fan, Stan Z. Li

  96. Adversarial Weight Perturbation Improves Generalization in Graph Neural Networks

    Yihan Wu, Aleksandar Bojchevski, Heng Huang

  97. GraphPrompt: Graph-Based Prompt Templates for Biomedical Synonym Prediction

    Hanwen Xu, Jiayou Zhang, Zhirui Wang, Shizhuo Zhang, Megh Bhalerao, Yucong Liu, Dawei Zhu, Sheng Wang

  98. Global Concept-Based Interpretability for Graph Neural Networks via Neuron Analysis

    Han Xuanyuan, Pietro Barbiero, Dobrik Georgiev, Lucie Charlotte Magister, Pietro Liò

  99. Reinforcement Causal Structure Learning on Order Graph

    Dezhi Yang, Guoxian Yu, Jun Wang, Zhengtian Wu, Maozu Guo

  100. Simple and Efficient Heterogeneous Graph Neural Network

    Xiaocheng Yang, Mingyu Yan, Shirui Pan, Xiaochun Ye, Dongrui Fan

  101. Cluster-Guided Contrastive Graph Clustering Network

    Xihong Yang, Yue Liu, Sihang Zhou, Siwei Wang, Wenxuan Tu, Qun Zheng, Xinwang Liu, Liming Fang, En Zhu

  102. Lifelong Compression Mixture Model via Knowledge Relationship Graph

    Fei Ye, Adrian G. Bors

  103. Random Walk Conformer: Learning Graph Representation from Long and Short Range

    Pei-Kai Yeh, Hsi-Wen Chen, Ming-Syan Chen

  104. Priori Anchor Labels Supervised Scalable Multi-View Bipartite Graph Clustering

    Jiali You, Zhenwen Ren, Xiaojian You, Haoran Li, Yuancheng Yao

  105. Substructure Aware Graph Neural Networks

    DingYi Zeng, Wanlong Liu, Wenyu Chen, Li Zhou, Malu Zhang, Hong Qu

  106. ImGCL: Revisiting Graph Contrastive Learning on Imbalanced Node Classification

    Liang Zeng, Lanqing Li, Ziqi Gao, Peilin Zhao, Jian Li

  107. DRGCN: Dynamic Evolving Initial Residual for Deep Graph Convolutional Networks

    Lei Zhang, Xiaodong Yan, Jianshan He, Ruopeng Li, Wei Chu

  108. Let the Data Choose: Flexible and Diverse Anchor Graph Fusion for Scalable Multi-View Clustering

    Pei Zhang, Siwei Wang, Liang Li, Changwang Zhang, Xinwang Liu, En Zhu, Zhe Liu, Lu Zhou, Lei Luo

  109. Spectral Feature Augmentation for Graph Contrastive Learning and Beyond

    Yifei Zhang, Hao Zhu, Zixing Song, Piotr Koniusz, Irwin King

  110. Dynamic Heterogeneous Graph Attention Neural Architecture Search

    Zeyang Zhang, Ziwei Zhang, Xin Wang, Yijian Qin, Zhou Qin, Wenwu Zhu

  111. Tensorized Incomplete Multi-View Clustering with Intrinsic Graph Completion

    Shuping Zhao, Jie Wen, Lunke Fei, Bob Zhang

  112. Data Imputation with Iterative Graph Reconstruction

    Jiajun Zhong, Ning Gui, Weiwei Ye

  113. Principled and Efficient Motif Finding for Structure Learning of Lifted Graphical Models

    Jonathan Feldstein, Dominic Phillips, Efthymia Tsamoura

  114. Fair Short Paths in Vertex-Colored Graphs

    Matthias Bentert, Leon Kellerhals, Rolf Niedermeier

  115. GRASMOS: Graph Signage Model Selection for Gene Regulatory Networks

    Angelina Brilliantova, Hannah Miller, Ivona Bezáková

  116. Reviewing Labels: Label Graph Network with Top-k Prediction Set for Relation Extraction

    Bo Li, Wei Ye, Jinglei Zhang, Shikun Zhang

  117. Graph Component Contrastive Learning for Concept Relatedness Estimation

    Yueen Ma, Zixing Song, Xuming Hu, Jingjing Li, Yifei Zhang, Irwin King

  118. Improving Interpretability via Explicit Word Interaction Graph Layer

    Arshdeep Sekhon, Hanjie Chen, Aman Shrivastava, Zhe Wang, Yangfeng Ji, Yanjun Qi

  119. Exploring Faithful Rationale for Multi-Hop Fact Verification via Salience-Aware Graph Learning

    Jiasheng Si, Yingjie Zhu, Deyu Zhou

  120. Continual Graph Convolutional Network for Text Classification

    Tiandeng Wu, Qijiong Liu, Yi Cao, Yao Huang, Xiao-Ming Wu, Jiandong Ding

  121. Orders Are Unwanted: Dynamic Deep Graph Convolutional Network for Personality Detection

    Tao Yang, Jinghao Deng, Xiaojun Quan, Qifan Wang

  1. Towards Open Temporal Graph Neural Networks

    Kaituo Feng, Changsheng Li, Xiaolu Zhang, JUN ZHOU

  2. AutoGT: Automated Graph Transformer Architecture Search

    Zizhao Zhang, Xin Wang, Chaoyu Guan, Ziwei Zhang, Haoyang Li, Wenwu Zhu

  3. Rethinking the Expressive Power of GNNs via Graph Biconnectivity

    Bohang Zhang, Shengjie Luo, Liwei Wang, Di He

  4. Graph Neural Networks for Link Prediction with Subgraph Sketching

    Benjamin Paul Chamberlain, Sergey Shirobokov, Emanuele Rossi, Fabrizio Frasca, Thomas Markovich, Nils Yannick Hammerla, Michael M. Bronstein, Max Hansmire

  5. Do We Really Need Complicated Model Architectures For Temporal Networks?

    Weilin Cong, Si Zhang, Jian Kang, Baichuan Yuan, Hao Wu, Xin Zhou, Hanghang Tong, Mehrdad Mahdavi

  6. Learning on Large-scale Text-attributed Graphs via Variational Inference

    Jianan Zhao, Meng Qu, Chaozhuo Li, Hao Yan, Qian Liu, Rui Li, Xing Xie, Jian Tang

  7. Temporal Domain Generalization with Drift-Aware Dynamic Neural Networks

    Guangji Bai, Chen Ling, Liang Zhao

  8. Learning Fair Graph Representations via Automated Data Augmentations

    Hongyi Ling, Zhimeng Jiang, Youzhi Luo, Shuiwang Ji, Na Zou

  9. Spectral Augmentation for Self-Supervised Learning on Graphs

    Lu Lin, Jinghui Chen, Hongning Wang

  10. Serving Graph Compression for Graph Neural Networks

    Si Si, Felix Yu, Ankit Singh Rawat, Cho-Jui Hsieh, Sanjiv Kumar

  11. Effects of Graph Convolutions in Multi-layer Networks

    Aseem Baranwal, Kimon Fountoulakis, Aukosh Jagannath

  12. LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation

    Xuheng Cai, Chao Huang, Lianghao Xia, Xubin Ren

  13. Relational Attention: Generalizing Transformers for Graph-Structured Tasks

    Cameron Diao, Ricky Loynd

  14. Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs

    Yi-Lun Liao, Tess Smidt

  15. Learning rigid dynamics with face interaction graph networks

    Kelsey R Allen, Yulia Rubanova, Tatiana Lopez-Guevara, William F Whitney, Alvaro Sanchez-Gonzalez, Peter Battaglia, Tobias Pfaff

  16. Relational Attention: Generalizing Transformers for Graph-Structured Tasks

    Cameron Diao, Ricky Loynd

  17. Sign and Basis Invariant Networks for Spectral Graph Representation Learning

    Derek Lim, Joshua David Robinson, Lingxiao Zhao, Tess Smidt, Suvrit Sra, Haggai Maron, Stefanie Jegelka

  18. ExpressivE: A Spatio-Functional Embedding For Knowledge Graph Completion

    Aleksandar Pavlović, Emanuel Sallinger

  19. Learning MLPs on Graphs: A Unified View of Effectiveness, Robustness, and Efficiency

    Yijun Tian, Chuxu Zhang, Zhichun Guo, Xiangliang Zhang, Nitesh Chawla

  20. DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion

    Qitian Wu, Chenxiao Yang, Wentao Zhao, Yixuan He, David Wipf, Junchi Yan

  21. On Representing Linear Programs by Graph Neural Networks

    Ziang Chen, Jialin Liu, Xinshang Wang, Wotao Yin

  22. ACMP: Allen-Cahn Message Passing with Attractive and Repulsive Forces for Graph Neural Networks

    Yuelin Wang, Kai Yi, Xinliang Liu, Yu Guang Wang, Shi Jin

  23. MeshDiffusion: Score-based Generative 3D Mesh Modeling

    Zhen Liu, Yao Feng, Michael J. Black, Derek Nowrouzezahrai, Liam Paull, Weiyang Liu

  24. LMC: Fast Training of GNNs via Subgraph Sampling with Provable Convergence

    Zhihao Shi, Xize Liang, Jie Wang

  25. Learning Controllable Adaptive Simulation for Multi-resolution Physics

    Tailin Wu, Takashi Maruyama, Qingqing Zhao, Gordon Wetzstein, Jure Leskovec

  26. Automated Data Augmentations for Graph Classification

    Youzhi Luo, Michael Curtis McThrow, Wing Yee Au, Tao Komikado, Kanji Uchino, Koji Maruhashi, Shuiwang Ji

  27. Chasing All-Round Graph Representation Robustness: Model, Training, and Optimization

    Chunhui Zhang, Yijun Tian, Mingxuan Ju, Zheyuan Liu, Yanfang Ye, Nitesh Chawla, Chuxu Zhang

  28. Revisiting Graph Adversarial Attack and Defense From a Data Distribution Perspective

    Kuan Li, Yang Liu, Xiang Ao, Qing He

  29. Agent-based Graph Neural Networks

    Karolis Martinkus, Pál András Papp, Benedikt Schesch, Roger Wattenhofer

  30. Characterizing the Influence of Graph Elements

    Zizhang Chen, Peizhao Li, Hongfu Liu, Pengyu Hong

  31. Limitless Stability for Graph Convolutional Networks

    Christian Koke

  32. NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs

    Jinsong Chen, Kaiyuan Gao, Gaichao Li, Kun He

  33. Empowering Graph Representation Learning with Test-Time Graph Transformation

    Wei Jin, Tong Zhao, Jiayuan Ding, Yozen Liu, Jiliang Tang, Neil Shah

  34. N-WL: A New Hierarchy of Expressivity for Graph Neural Networks

    Qing Wang, Dillon Ze Chen, Asiri Wijesinghe, Shouheng Li, Muhammad Farhan

  35. Are More Layers Beneficial to Graph Transformers?

    Haiteng Zhao, Shuming Ma, Dongdong Zhang, Zhi-Hong Deng, Furu Wei

  36. Strategic Classification with Graph Neural Networks

    Itay Eilat, Ben Finkelshtein, Chaim Baskin, Nir Rosenfeld

  37. Robust Graph Dictionary Learning

    Weijie Liu, Jiahao Xie, Chao Zhang, Makoto Yamada, Nenggan Zheng, Hui Qian

  38. Specformer: Spectral Graph Neural Networks Meet Transformers

    Deyu Bo, Chuan Shi, Lele Wang, Renjie Liao

  39. DiGress: Discrete Denoising diffusion for graph generation

    Clement Vignac, Igor Krawczuk, Antoine Siraudin, Bohan Wang, Volkan Cevher, Pascal Frossard

  40. LogicDP: Creating Labels for Graph Data via Inductive Logic Programming

    Yuan Yang, Faramarz Fekri, James Clayton Kerce, Ali Payani

  41. Graph Neural Network-Inspired Kernels for Gaussian Processes in Semi-Supervised Learning

    Zehao Niu, Mihai Anitescu, Jie Chen

  42. Explaining Temporal Graph Models through an Explorer-Navigator Framework

    Wenwen Xia, Mincai Lai, Caihua Shan, Yao Zhang, Xinnan Dai, Xiang Li, Dongsheng Li

  43. Learning Symbolic Models for Graph-structured Physical Mechanism

    Hongzhi Shi, Jingtao Ding, Yufan Cao, quanming yao, Li Liu, Yong Li

  44. Efficient Model Updates for Approximate Unlearning of Graph-Structured Data

    Eli Chien, Chao Pan, Olgica Milenkovic

  45. Imitating Graph-Based Planning with Goal-Conditioned Policies

    Junsu Kim, Younggyo Seo, Sungsoo Ahn, Kyunghwan Son, Jinwoo Shin

  46. MetaGL: Evaluation-Free Selection of Graph Learning Models via Meta-Learning

    Namyong Park, Ryan A. Rossi, Nesreen Ahmed, Christos Faloutsos

  47. On Compositional Uncertainty Quantification for Seq2seq Graph Parsing

    Zi Lin, Du Phan, Panupong Pasupat, Jeremiah Zhe Liu, Jingbo Shang

  48. Searching Lottery Tickets in Graph Neural Networks: A Dual Perspective

    Kun Wang, Yuxuan Liang, Pengkun Wang, Xu Wang, Pengfei Gu, Junfeng Fang, Yang Wang

  49. Grounding Graph Network Simulators using Physical Sensor Observations

    Jonas Linkerhägner, Niklas Freymuth, Paul Maria Scheikl, Franziska Mathis-Ullrich, Gerhard Neumann

  50. Graph Contrastive Learning for Skeleton-based Action Recognition

    Xiaohu Huang, Hao Zhou, Jian Wang, Haocheng Feng, Junyu Han, Errui Ding, Jingdong Wang, Xinggang Wang, Wenyu Liu, Bin Feng

  51. A Graph Neural Network Approach to Automated Model Building in Cryo-EM Maps

    Kiarash Jamali, Dari Kimanius, Sjors HW Scheres

  52. Energy-based Out-of-Distribution Detection for Graph Neural Networks

    Qitian Wu, Yiting Chen, Chenxiao Yang, Junchi Yan

  53. Rethinking Graph Lottery Tickets: Graph Sparsity Matters

    Bo Hui, Da Yan, Xiaolong Ma, Wei-Shinn Ku

  54. Enhancing the Inductive Biases of Graph Neural ODE for Modeling Physical Systems

    Suresh Bishnoi, Ravinder Bhattoo, Jayadeva Jayadeva, Sayan Ranu, N M Anoop Krishnan

  55. Learning Heterogeneous Interaction Strengths by Trajectory Prediction with Graph Neural Network

    Seungwoong Ha, Hawoong Jeong

  56. GReTo: Remedying dynamic graph topology-task discordance via target homophily

    Zhengyang Zhou, qihe huang, Gengyu Lin, Kuo Yang, LEI BAI, Yang Wang

  57. Learnable Topological Features For Phylogenetic Inference via Graph Neural Networks

    Cheng Zhang

  58. Unveiling the sampling density in non-uniform geometric graphs

    Raffaele Paolino, Aleksandar Bojchevski, Stephan Günnemann, Gitta Kutyniok, Ron Levie

  59. Multi-task Self-supervised Graph Neural Networks Enable Stronger Task Generalization

    Mingxuan Ju, Tong Zhao, Qianlong Wen, Wenhao Yu, Neil Shah, Yanfang Ye, Chuxu Zhang

  60. Mole-BERT: Rethinking Pre-training Graph Neural Networks for Molecules

    Jun Xia, Chengshuai Zhao, Bozhen Hu, Zhangyang Gao, Cheng Tan, Yue Liu, Siyuan Li, Stan Z. Li

  61. Diffusion Models for Causal Discovery via Topological Ordering

    Pedro Sanchez, Xiao Liu, Alison Q O'Neil, Sotirios A. Tsaftaris

  62. Value Memory Graph: A Graph-Structured World Model for Offline Reinforcement Learning

    Deyao Zhu, Li Erran Li, Mohamed Elhoseiny

  63. FoSR: First-order spectral rewiring for addressing oversquashing in GNNs

    Kedar Karhadkar, Pradeep Kr. Banerjee, Guido Montufar

  64. Joint Edge-Model Sparse Learning is Provably Efficient for Graph Neural Networks

    Shuai Zhang, Meng Wang, Pin-Yu Chen, Sijia Liu, Songtao Lu, Miao Liu

  65. Revisiting Robustness in Graph Machine Learning

    Lukas Gosch, Daniel Sturm, Simon Geisler, Stephan Günnemann

  66. Learnable Graph Convolutional Attention Networks

    Adrián Javaloy, Pablo Sanchez Martin, Amit Levi, Isabel Valera

  67. Matching receptor to odorant with protein language and graph neural networks

    Matej Hladiš, Maxence Lalis, Sebastien Fiorucci, Jérémie Topin

  68. Synthetic Data Generation of Many-to-Many Datasets via Random Graph Generation

    Kai Xu, Georgi Ganev, Emile Joubert, Rees Davison, Olivier Van Acker, Luke Robinson

  69. A critical look at the evaluation of GNNs under heterophily: Are we really making progress?

    Oleg Platonov, Denis Kuznedelev, Michael Diskin, Artem Babenko, Liudmila Prokhorenkova

  70. Fair Attribute Completion on Graph with Missing Attributes

    Dongliang Guo, Zhixuan Chu, Sheng Li

  71. Multimodal Analogical Reasoning over Knowledge Graphs

    Ningyu Zhang, Lei Li, Xiang Chen, Xiaozhuan Liang, Shumin Deng, Huajun Chen

  72. Global Explainability of GNNs via Logic Combination of Learned Concepts

    Steve Azzolin, Antonio Longa, Pietro Barbiero, Pietro Lio, Andrea Passerini

  73. GNNDelete: A General Strategy for Unlearning in Graph Neural Networks

    Jiali Cheng, George Dasoulas, Huan He, Chirag Agarwal, Marinka Zitnik

  74. A2Q: Aggregation-Aware Quantization for Graph Neural Networks

    Zeyu Zhu, Fanrong Li, Zitao Mo, Qinghao Hu, Gang Li, Zejian Liu, Xiaoyao Liang, Jian Cheng

  75. Graph Domain Adaptation via Theory-Grounded Spectral Regularization

    Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen

  76. Learning Hierarchical Protein Representations via Complete 3D Graph Networks

    Limei Wang, Haoran Liu, Yi Liu, Jerry Kurtin, Shuiwang Ji

  77. Unbiased Stochastic Proximal Solver for Graph Neural Networks with Equilibrium States

    Mingjie Li, Yifei Wang, Yisen Wang, Zhouchen Lin

  78. Cycle to Clique (Cy2C) Graph Neural Network: A Sight to See beyond Neighborhood Aggregation

    Yun Young Choi, Sun Woo Park, Youngho Woo, U Jin Choi

  79. A Non-Asymptotic Analysis of Oversmoothing in Graph Neural Networks

    Xinyi Wu, Zhengdao Chen, William Wei Wang, Ali Jadbabaie

  80. Anti-Symmetric DGN: a stable architecture for Deep Graph Networks

    Alessio Gravina, Davide Bacciu, Claudio Gallicchio

  81. GNNInterpreter: A Probabilistic Generative Model-Level Explanation for Graph Neural Networks

    Xiaoqi Wang, Han Wei Shen

  82. Edgeformers: Graph-Empowered Transformers for Representation Learning on Textual-Edge Networks

    Bowen Jin, Yu Zhang, Yu Meng, Jiawei Han

  83. Direct Embedding of Temporal Network Edges via Time-Decayed Line Graphs

    Sudhanshu Chanpuriya, Ryan A. Rossi, Sungchul Kim, Tong Yu, Jane Hoffswell, Nedim Lipka, Shunan Guo, Cameron N Musco

  84. Protein Representation Learning via Knowledge Enhanced Primary Structure Reasoning

    Hong-Yu Zhou, Yunxiang Fu, Zhicheng Zhang, Bian Cheng, Yizhou Yu

  85. Graph-based Deterministic Policy Gradient for Repetitive Combinatorial Optimization Problems

    Zhongyuan Zhao, Ananthram Swami, Santiago Segarra

  86. Anisotropic Message Passing: Graph Neural Networks with Directional and Long-Range Interactions

    Moritz Thürlemann, Sereina Riniker

  87. CktGNN: Circuit Graph Neural Network for Electronic Design Automation

    Zehao Dong, Weidong Cao, Muhan Zhang, Dacheng Tao, Yixin Chen, Xuan Zhang

  88. Confidence-Based Feature Imputation for Graphs with Partially Known Features

    Daeho Um, Jiwoong Park, Seulki Park, Jin young Choi

  89. Causal Representation Learning for Instantaneous and Temporal Effects in Interactive Systems

    Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M Asano, Taco Cohen, Efstratios Gavves

  90. Neural Compositional Rule Learning for Knowledge Graph Reasoning

    Kewei Cheng, Nesreen Ahmed, Yizhou Sun

  91. DAG Matters! GFlowNets Enhanced Explainer for Graph Neural Networks

    Wenqian Li, Yinchuan Li, Zhigang Li, Jianye HAO, Yan Pang

  92. On Representing Mixed-Integer Linear Programs by Graph Neural Networks

    Ziang Chen, Jialin Liu, Xinshang Wang, Wotao Yin

  93. UniKGQA: Unified Retrieval and Reasoning for Solving Multi-hop Question Answering Over Knowledge Graph

    Jinhao Jiang, Kun Zhou, Xin Zhao, Ji-Rong Wen

  94. Boosting the Cycle Counting Power of Graph Neural Networks with I2-GNNs

    Yinan Huang, Xingang Peng, Jianzhu Ma, Muhan Zhang

  95. AutoTransfer: AutoML with Knowledge Transfer - An Application to Graph Neural Networks

    Kaidi Cao, Jiaxuan You, Jiaju Liu, Jure Leskovec

  96. Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs

    Chenxiao Yang, Qitian Wu, Jiahua Wang, Junchi Yan

  97. Subsampling in Large Graphs Using Ricci Curvature

    Shushan Wu, Huimin Cheng, Jiazhang Cai, Ping Ma, Wenxuan Zhong

  98. Spacetime Representation Learning

    Marc T. Law, James Lucas

  99. Logical Entity Representation in Knowledge-Graphs for Differentiable Rule Learning

    Chi Han, Qizheng He, Charles Yu, Xinya Du, Hanghang Tong, Heng Ji

  100. MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization

    Xiaotian Han, Tong Zhao, Yozen Liu, Xia Hu, Neil Shah

  101. A Message Passing Perspective on Learning Dynamics of Contrastive Learning

    Yifei Wang, Qi Zhang, Tianqi Du, Jiansheng Yang, Zhouchen Lin, Yisen Wang

  102. A Differential Geometric View and Explainability of GNN on Evolving Graphs

    Yazheng Liu, Xi Zhang, Sihong Xie

  103. Link Prediction with Non-Contrastive Learning

    William Shiao, Zhichun Guo, Tong Zhao, Evangelos E. Papalexakis, Yozen Liu, Neil Shah

  104. Learning to Induce Causal Structure

    Nan Rosemary Ke, Silvia Chiappa, Jane X Wang, Jorg Bornschein, Anirudh Goyal, Melanie Rey, Theophane Weber, Matthew Botvinick, Michael Curtis Mozer, Danilo Jimenez Rezende

  105. Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing

    Yunchong Song, Chenghu Zhou, Xinbing Wang, Zhouhan Lin

  106. Logical Message Passing Networks with One-hop Inference on Atomic Formulas

    Zihao Wang, Yangqiu Song, Ginny Wong, Simon See

  107. Fundamental Limits in Formal Verification of Message-Passing Neural Networks

    Marco Sälzer, Martin Lange

  108. Robust Scheduling with GFlowNets

    David W Zhang, Corrado Rainone, Markus Peschl, Roberto Bondesan

  109. Hierarchical Relational Learning for Few-Shot Knowledge Graph Completion

    Han Wu, Jie Yin, Bala Rajaratnam, Jianyuan Guo

  110. O-GNN: incorporating ring priors into molecular modeling

    Jinhua Zhu, Kehan Wu, Bohan Wang, Yingce Xia, Shufang Xie, Qi Meng, Lijun Wu, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu

  111. Molecule Generation For Target Protein Binding with Structural Motifs

    ZAIXI ZHANG, Yaosen Min, Shuxin Zheng, Qi Liu

  112. A GNN-Guided Predict-and-Search Framework for Mixed-Integer Linear Programming

    Qingyu Han, Linxin Yang, Qian Chen, Xiang Zhou, Dong Zhang, Akang Wang, Ruoyu Sun, Xiaodong Luo

  113. Label Propagation with Weak Supervision

    Rattana Pukdee, Dylan Sam, Pradeep Kumar Ravikumar, Nina Balcan

  114. ContraNorm: A Contrastive Learning Perspective on Oversmoothing and Beyond

    Xiaojun Guo, Yifei Wang, Tianqi Du, Yisen Wang

  115. Diffusion Probabilistic Modeling of Protein Backbones in 3D for the motif-scaffolding problem

    Brian L. Trippe, Jason Yim, Doug Tischer, David Baker, Tamara Broderick, Regina Barzilay, Tommi S. Jaakkola

  116. On Explaining Neural Network Robustness with Activation Path

    Ziping Jiang

  117. Equivariant Hypergraph Diffusion Neural Operators

    Peihao Wang, Shenghao Yang, Yunyu Liu, Zhangyang Wang, Pan Li

  118. Interpretable Geometric Deep Learning via Learnable Randomness Injection

    Siqi Miao, Yunan Luo, Mia Liu, Pan Li

  119. Protein Representation Learning by Geometric Structure Pretraining

    Zuobai Zhang, Minghao Xu, Arian Rokkum Jamasb, Vijil Chenthamarakshan, Aurelie Lozano, Payel Das, Jian Tang

  120. Leveraging Future Relationship Reasoning for Vehicle Trajectory Prediction

    Daehee Park, Hobin Ryu, Yunseo Yang, Jegyeong Cho, Jiwon Kim, Kuk-Jin Yoon

  121. TILP: Differentiable Learning of Temporal Logical Rules on Knowledge Graphs

    Siheng Xiong, Yuan Yang, Faramarz Fekri, James Clayton Kerce

  122. Boosting Causal Discovery via Adaptive Sample Reweighting

    An Zhang, Fangfu Liu, Wenchang Ma, Zhibo Cai, Xiang Wang, Tat-Seng Chua

  1. BLADE: Biased Neighborhood Sampling based Graph Neural Network for Directed Graphs

    Srinivas Virinchi, Anoop Saladi

  2. Simplifying Graph-based Collaborative Filtering for Recommendation

    Li He, Xianzhi Wang, Dingxian Wang, Haoyuan Zou, Hongzhi Yin, Guandong Xu

  3. Self-Supervised Group Graph Collaborative Filtering for Group Recommendation

    Kang Li, Chang-Dong Wang, Jian-Huang Lai, Huaqiang Yuan

  4. Minimum Entropy Principle Guided Graph Neural Networks

    Zhenyu Yang, Ge Zhang, Jia Wu, Jian Yang, Quan Z. Sheng, Hao Peng, Angsheng Li, Shan Xue, Jianlin Su

  5. Learning to Distill Graph Neural Networks

    Cheng Yang, Yuxin Guo, Yao Xu, Chuan Shi, Jiawei Liu, Chunchen Wang, Xin Li, Ning Guo, Hongzhi Yin

  6. MM-GNN: Mix-Moment Graph Neural Network towards Modeling Neighborhood Feature Distribution

    Wendong Bi, Lun Du, Qiang Fu, Yanlin Wang, Shi Han, Dongmei Zhang

  7. Global Counterfactual Explainer for Graph Neural Networks

    Zexi Huang, Mert Kosan, Sourav Medya, Sayan Ranu, Ambuj K. Singh

  8. Effective Graph Kernels for Evolving Functional Brain Networks

    Xinlei Wang, Jinyi Chen, Bing Tian Dai, Junchang Xin, Yu Gu, Ge Yu

  9. Self-Supervised Graph Structure Refinement for Graph Neural Networks

    Jianan Zhao, Qianlong Wen, Mingxuan Ju, Chuxu Zhang, Yanfang Ye

  10. Learning Stance Embeddings from Signed Social Graphs

    John Pougué-Biyong, Akshay Gupta, Aria Haghighi, Ahmed El-Kishky

  11. Variational Reasoning over Incomplete Knowledge Graphs for Conversational Recommendation

    Xiaoyu Zhang, Xin Xin, Dongdong Li, Wenxuan Liu, Pengjie Ren, Zhumin Chen, Jun Ma, Zhaochun Ren

  12. A Multi-graph Fusion Based Spatiotemporal Dynamic Learning Framework

    Xu Wang, Lianliang Chen, Hongbo Zhang, Pengkun Wang, Zhengyang Zhou, Yang Wang

  13. Simultaneous Linear Multi-view Attributed Graph Representation Learning and Clustering

    Chakib Fettal, Lazhar Labiod, Mohamed Nadif

  14. Interpretable Research Interest Shift Detection with Temporal Heterogeneous Graphs

    Qiang Yang, Changsheng Ma, Qiannan Zhang, Xin Gao, Chuxu Zhang, Xiangliang Zhang

  15. Self-supervised Graph Representation Learning for Black Market Account Detection

    Zequan Xu, Lianyun Li, Hui Li, Qihang Sun, Shaofeng Hu, Rongrong Ji

  16. GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection

    Yixin Liu, Kaize Ding, Huan Liu, Shirui Pan

  17. Alleviating Structural Distribution Shift in Graph Anomaly Detection

    Yuan Gao, Xiang Wang, Xiangnan He, Zhenguang Liu, Huamin Feng, Yongdong Zhang

  18. Cognition-aware Knowledge Graph Reasoning for Explainable Recommendation

    Qingyu Bing, Qiannan Zhu, Zhicheng Dou

  19. DisenPOI: Disentangling Sequential and Geographical Influence for Point-of-Interest Recommendation

    Yifang Qin, Yifan Wang, Fang Sun, Wei Ju, Xuyang Hou, Zhe Wang, Jia Cheng, Jun Lei, Ming Zhang

  20. VRKG4Rec: Virtual Relational Knowledge Graph for Recommendation

    Lingyun Lu, Bang Wang, Zizhuo Zhang, Shenghao Liu, Han Xu

  21. Heterogeneous Graph Contrastive Learning for Recommendation

    Mengru Chen, Chao Huang, Lianghao Xia, Wei Wei, Yong Xu, Ronghua Luo

  22. SGCCL: Siamese Graph Contrastive Consensus Learning for Personalized Recommendation

    Boyu Li, Ting Guo, Xingquan Zhu, Qian Li, Yang Wang, Fang Chen

  23. Robust Training of Graph Neural Networks via Noise Governance

    Siyi Qian, Haochao Ying, Renjun Hu, Jingbo Zhou, Jintai Chen, Danny Z. Chen, Jian Wu

  24. Cooperative Explanations of Graph Neural Networks

    Junfeng Fang, Xiang Wang, An Zhang, Zemin Liu, Xiangnan He, Tat-Seng Chua

  25. Bring Your Own View: Graph Neural Networks for Link Prediction with Personalized Subgraph Selection

    Qiaoyu Tan, Xin Zhang, Ninghao Liu, Daochen Zha, Li Li, Rui Chen, Soo-Hyun Choi, Xia Hu

  26. Towards Faithful and Consistent Explanations for Graph Neural Networks

    Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang

  27. Position-Aware Subgraph Neural Networks with Data-Efficient Learning

    Chang Liu, Yuwen Yang, Zhe Xie, Hongtao Lu, Yue Ding

  28. Graph Neural Networks with Interlayer Feature Representation for Image Super-Resolution

    Shenggui Tang, Kaixuan Yao, Jianqing Liang, Zhiqiang Wang, Jiye Liang

  29. DGRec: Graph Neural Network for Recommendation with Diversified Embedding Generation

    Liangwei Yang, Shengjie Wang, Yunzhe Tao, Jiankai Sun, Xiaolong Liu, Philip S. Yu, Taiqing Wang

  30. Inductive Graph Transformer for Delivery Time Estimation

    Xin Zhou, Jinglong Wang, Yong Liu, Xingyu Wu, Zhiqi Shen, Cyril Leung

  31. Search Behavior Prediction: A Hypergraph Perspective

    Yan Han, Edward W. Huang, Wenqing Zheng, Nikhil Rao, Zhangyang Wang, Karthik Subbian

  32. Directed Acyclic Graph Factorization Machines for CTR Prediction via Knowledge Distillation

    Zhen Tian, Ting Bai, Zibin Zhang, Zhiyuan Xu, Kangyi Lin, Ji-Rong Wen, Wayne Xin Zhao

  33. Heterogeneous Graph-based Context-aware Document Ranking

    Shuting Wang, Zhicheng Dou, Yutao Zhu

  34. Graph Summarization via Node Grouping: A Spectral Algorithm

    Arpit Merchant, Michael Mathioudakis, Yanhao Wang

  35. Ranking-based Group Identification via Factorized Attention on Social Tripartite Graph

    Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu

  36. Graph Sequential Neural ODE Process for Link Prediction on Dynamic and Sparse Graphs

    Linhao Luo, Gholamreza Haffari, Shirui Pan

  37. S2GAE: Self-Supervised Graph Autoencoders are Generalizable Learners with Graph Masking

    Qiaoyu Tan, Ninghao Liu, Xiao Huang, Soo-Hyun Choi, Li Li, Rui Chen, Xia Hu

  38. Combining vs. Transferring Knowledge: Investigating Strategies for Improving Demographic Inference in Low Resource Settings

    Yaguang Liu, Lisa Singh

  39. Active Ensemble Learning for Knowledge Graph Error Detection

    Junnan Dong, Qinggang Zhang, Xiao Huang, Qiaoyu Tan, Daochen Zha, Zihao Zhao

  40. Stochastic Solutions for Dense Subgraph Discovery in Multilayer Networks

    Yasushi Kawase, Atsushi Miyauchi, Hanna Sumita

  41. Modeling Fine-grained Information via Knowledge-aware Hierarchical Graph for Zero-shot Entity Retrieval

    Taiqiang Wu, Xingyu Bai, Weigang Guo, Weijie Liu, Siheng Li, Yujiu Yang

  42. Web of Conferences: A Conference Knowledge Graph

    Shuo Yu, Ciyuan Peng, Chengchuan Xu, Chen Zhang, Feng Xia

  43. Developing and Evaluating Graph Counterfactual Explanation with GRETEL

    Mario Alfonso Prado-Romero, Bardh Prenkaj, Giovanni Stilo

  44. Generalizing Graph Neural Network across Graphs and Time

    Zhihao Wen

  45. Graphs: Privacy and Generation through ML

    Rucha Bhalchandra Joshi

  46. Data-Efficient Graph Learning Meets Ethical Challenges

    Tao Tang

  47. From Classic GNNs to Hyper-GNNs for Detecting Camouflaged Malicious Actors

    Venus Haghighi

  48. Efficient Graph Learning for Anomaly Detection Systems

    Falih Gozi Febrinanto

  1. GELTOR: A Graph Embedding Method based on Listwise Learning to Rank

    Masoud Reyhani Hamedani, Jin-Su Ryu, Sang-Wook Kim

  2. Graph-less Collaborative Filtering

    Lianghao Xia, Chao Huang, Jiao Shi, Yong Xu

  3. Fair Graph Representation Learning via Diverse Mixture-of-Experts

    Zheyuan Liu, Chunhui Zhang, Yijun Tian, Erchi Zhang, Chao Huang, Yanfang Ye, Chuxu Zhang

  4. Multi-Aspect Heterogeneous Graph Augmentation

    Yuchen Zhou, Yanan Cao, Yongchao Liu, Yanmin Shang, Peng Zhang, Zheng Lin, Yun Yue, Baokun Wang, Xing Fu, Weiqiang Wang

  5. RSGNN: A Model-agnostic Approach for Enhancing the Robustness of Signed Graph Neural Networks

    Zeyu Zhang, Jiamou Liu, Xianda Zheng, Yifei Wang, Pengqian Han, Yupan Wang, Kaiqi Zhao, Zijian Zhang

  6. Collaboration-Aware Graph Convolutional Network for Recommender Systems

    Yu Wang, Yuying Zhao, Yi Zhang, Tyler Derr

  7. Hierarchical Knowledge Graph Learning Enabled Socioeconomic Indicator Prediction in Location-Based Social Network

    Zhilun Zhou, Yu Liu, Jingtao Ding, Depeng Jin, Yong Li

  8. SeeGera: Self-supervised Semi-implicit Graph Variational Auto-encoders with Masking

    Xiang Li, Tiandi Ye, Caihua Shan, Dongsheng Li, Ming Gao

  9. Graph Self-supervised Learning with Augmentation-aware Contrastive Learning

    Dong Chen, Xiang Zhao, Wei Wang, Zhen Tan, Weidong Xiao

  10. Enhancing Hierarchy-Aware Graph Networks with Deep Dual Clustering for Session-based Recommendation

    Jiajie Su, Chaochao Chen, Weiming Liu, Fei Wu, Xiaolin Zheng, Haoming Lyu

  11. Unifying and Improving Graph Convolutional Neural Networks with Wavelet Denoising Filters

    Liangtian Wan, Xiaona Li, Huijin Han, Xiaoran Yan, Lu Sun, Zhaolong Ning, Feng Xia

  12. SINCERE: Sequential Interaction Networks representation learning on Co-Evolving RiEmannian manifolds

    Junda Ye, Zhongbao Zhang, Li Sun, Yang Yan, Feiyang Wang, Fuxin Ren

  13. GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks

    Zemin Liu, Xingtong Yu, Yuan Fang, Xinming Zhang

  14. An Attentional Multi-scale Co-evolving Model for Dynamic Link Prediction

    Guozhen Zhang, Tian Ye, Depeng Jin, Yong Li

  15. Robust Graph Representation Learning for Local Corruption Recovery

    Bingxin Zhou, Yuanhong Jiang, Yuguang Wang, Jingwei Liang, Junbin Gao, Shirui Pan, Xiaoqun Zhang

  16. Intra and Inter Domain HyperGraph Convolutional Network for Cross-Domain Recommendation

    Zhongxuan Han, Xiaolin Zheng, Chaochao Chen, Wenjie Cheng, Yang Yao

  17. Hyperbolic Geometric Graph Representation Learning for Hierarchy-imbalance Node Classification

    Xingcheng Fu, Yuecen Wei, Qingyun Sun, Haonan Yuan, Jia Wu, Hao Peng, Jianxin Li

  18. Graph Neural Networks without Propagation

    Liang Yang, Qiuliang Zhang, Runjie Shi, Wenmiao Zhou, Bingxin Niu, Chuan Wang, Xiaochun Cao, Dongxiao He, Zhen Wang, Yuanfang Guo

  19. TIGER: Temporal Interaction Graph Embedding with Restarts

    Yao Zhang, Yun Xiong, Yongxiang Liao, Yiheng Sun, Yucheng Jin, Xuehao Zheng, Yangyong Zhu

  20. Self-Supervised Teaching and Learning of Representations on Graphs

    Liangtian Wan, Zhenqiang Fu, Lu Sun, Xianpeng Wang, Gang Xu, Xiaoran Yan, Feng Xia

  21. SE-GSL: A General and Effective Graph Structure Learning Framework through Structural Entropy Optimization

    Dongcheng Zou, Hao Peng, Xiang Huang, Renyu Yang, Jianxin Li, Jia Wu, Chunyang Liu, Philip S. Yu

  22. Homophily-oriented Heterogeneous Graph Rewiring

    Jiayan Guo, Lun Du, Wendong Bi, Qiang Fu, Xiaojun Ma, Xu Chen, Shi Han, Dongmei Zhang, Yan Zhang

  23. HGWaveNet: A Hyperbolic Graph Neural Network for Temporal Link Prediction

    Qijie Bai, Changli Nie, Haiwei Zhang, Dongming Zhao, Xiaojie Yuan

  24. Rethinking Structural Encodings: Adaptive Graph Transformer for Node Classification Task

    Xiaojun Ma, Qin Chen, Yi Wu, Guojie Song, Liang Wang, Bo Zheng

  25. CMINet: a Graph Learning Framework for Content-aware Multi-channel Influence Diffusion

    Hsi-Wen Chen, De-Nian Yang, Wang-Chien Lee, Philip S. Yu, Ming-Syan Chen

  26. Federated Node Classification over Graphs with Latent Link-type Heterogeneity

    Han Xie, Li Xiong, Carl Yang

  27. Expressive and Efficient Representation Learning for Ranking Links in Temporal Graphs

    Susheel Suresh, Mayank Shrivastava, Arko Mukherjee, Jennifer Neville, Pan Li

  28. Semi-Supervised Embedding of Attributed Multiplex Networks

    Ylli Sadikaj, Justus Rass, Yllka Velaj, Claudia Plant

  29. Search to Capture Long-range Dependency with Stacking GNNs for Graph Classification

    Lanning Wei, Zhiqiang He, Huan Zhao, Quanming Yao

  30. HINormer: Representation Learning On Heterogeneous Information Networks with Graph Transformer

    Qiheng Mao, Zemin Liu, Chenghao Liu, Jianling Sun

  31. Auto-HeG: Automated Graph Neural Network on Heterophilic Graphs

    Xin Zheng, Miao Zhang, Chunyang Chen, Qin Zhang, Chuan Zhou, Shirui Pan

  32. Generating Counterfactual Hard Negative Samples for Graph Contrastive Learning

    Haoran Yang, Hongxu Chen, Sixiao Zhang, Xiangguo Sun, Qian Li, Xiangyu Zhao, Guandong Xu

  33. Minimum Topology Attacks for Graph Neural Networks

    Mengmei Zhang, Xiao Wang, Chuan Shi, Lingjuan Lyu, Tianchi Yang, Junping Du

  34. Multi-head Variational Graph Autoencoder Constrained by Sum-product Networks

    Riting Xia, Yan Zhang, Chunxu Zhang, Xueyan Liu, Bo Yang

  35. GIF: A General Graph Unlearning Strategy via Influence Function

    Jiancan Wu, Yi Yang, Yuchun Qian, Yongduo Sui, Xiang Wang, Xiangnan He

  36. INCREASE: Inductive Graph Representation Learning for Spatio-Temporal Kriging

    Chuanpan Zheng, Xiaoliang Fan, Cheng Wang, Jianzhong Qi, Chaochao Chen, Longbiao Chen

  37. Dual Intent Enhanced Graph Neural Network for Session-based New Item Recommendation

    Di Jin, Luzhi Wang, Yizhen Zheng, Guojie Song, Fei Jiang, Xiang Li, Wei Lin, Shirui Pan

  38. Toward Degree Bias in Embedding-Based Knowledge Graph Completion

    Harry Shomer, Wei Jin, Wentao Wang, Jiliang Tang

  39. Unlearning Graph Classifiers with Limited Data Resources

    Chao Pan, Eli Chien, Olgica Milenkovic

  40. KGTrust: Evaluating Trustworthiness of SIoT via Knowledge Enhanced Graph Neural Networks

    Zhizhi Yu, Di Jin, Cuiying Huo, Zhiqiang Wang, Xiulong Liu, Heng Qi, Jia Wu, Lingfei Wu

  41. GraphMAE2: A Decoding-Enhanced Masked Self-Supervised Graph Learner

    Zhenyu Hou, Yufei He, Yukuo Cen, Xiao Liu, Yuxiao Dong, Evgeny Kharlamov, Jie Tang

  42. CogDL: A Comprehensive Library for Graph Deep Learning

    Yukuo Cen, Zhenyu Hou, Yan Wang, Qibin Chen, Yizhen Luo, Zhongming Yu, Hengrui Zhang, Xingcheng Yao, Aohan Zeng, Shiguang Guo, Yuxiao Dong, Yang Yang, Peng Zhang, Guohao Dai, Yu Wang, Chang Zhou, Hongxia Yang, Jie Tang

  43. ApeGNN: Node-Wise Adaptive Aggregation in GNNs for Recommendation

    Dan Zhang, Yifan Zhu, Yuxiao Dong, Yuandong Wang, Wenzheng Feng, Evgeny Kharlamov, Jie Tang

  44. Anti-FakeU: Defending Shilling Attacks on Graph Neural Network based Recommender Model

    Xiaoyu You, Chi Li, Daizong Ding, Mi Zhang, Fuli Feng, Xudong Pan, Min Yang

  45. Compressed Interaction Graph based Framework for Multi-behavior Recommendation

    Wei Guo, Chang Meng, Enming Yuan, Zhicheng He, Huifeng Guo, Yingxue Zhang, Bo Chen, Yaochen Hu, Ruiming Tang, Xiu Li, Rui Zhang

  46. Correlative Preference Transfer with Hierarchical Hypergraph Network for Multi-Domain Recommendation

    Zixuan Xu, Penghui Wei, Shaoguo Liu, Weimin Zhang, Liang Wang, Bo Zheng

  47. Robust Preference-Guided Denoising for Graph based Social Recommendation

    Yuhan Quan, Jingtao Ding, Chen Gao, Lingling Yi, Depeng Jin, Yong Li

  48. Multi-Behavior Recommendation with Cascading Graph Convolution Networks

    Zhiyong Cheng, Sai Han, Fan Liu, Lei Zhu, Zan Gao, Yuxin Peng

  49. Personalized Graph Signal Processing for Collaborative Filtering

    Jiahao Liu, Dongsheng Li, Hansu Gu, Tun Lu, Peng Zhang, Li Shang, Ning Gu

  50. Dynamically Expandable Graph Convolution for Streaming Recommendation

    Bowei He, Xu He, Yingxue Zhang, Ruiming Tang, Chen Ma

  51. Dual Policy Learning for Aggregation Optimization in Graph Neural Network-based Recommender Systems

    Heesoo Jung, Sangpil Kim, Hogun Park

  52. Addressing Heterophily in Graph Anomaly Detection: A Perspective of Graph Spectrum

    Yuan Gao, Xiang Wang, Xiangnan He, Zhenguang Liu, Huamin Feng, Yongdong Zhang

  53. Node-wise Diffusion for Scalable Graph Learning

    Keke Huang, Jing Tang, Juncheng Liu, Renchi Yang, Xiaokui Xiao

  54. CitationSum: Citation-aware Graph Contrastive Learning for Scientific Paper Summarization

    Zheheng Luo, Qianqian Xie, Sophia Ananiadou

  55. MaSS: Model-agnostic, Semantic and Stealthy Data Poisoning Attack on Knowledge Graph Embedding

    Xiaoyu You, Beina Sheng, Daizong Ding, Mi Zhang, Xudong Pan, Min Yang, Fuli Feng

  56. Curriculum Graph Poisoning

    Hanwen Liu, Peilin Zhao, Tingyang Xu, Yatao Bian, Junzhou Huang, Yuesheng Zhu, Yadong Mu

  57. TFE-GNN: A Temporal Fusion Encoder Using Graph Neural Networks for Fine-grained Encrypted Traffic Classification

    Haozhen Zhang, Le Yu, Xi Xiao, Qing Li, Francesco Mercaldo, Xiapu Luo, Qixu Liu

  58. Unnoticeable Backdoor Attacks on Graph Neural Networks

    Enyan Dai, Minhua Lin, Xiang Zhang, Suhang Wang

  59. Quantifying and Defending against Privacy Threats on Federated Knowledge Graph Embedding

    Yuke Hu, Wei Liang, Ruofan Wu, Kai Xiao, Weiqiang Wang, Xiaochen Li, Jinfei Liu, Zhan Qin

  60. Event Prediction using Case-Based Reasoning over Knowledge Graphs

    Sola Shirai, Debarun Bhattacharjya, Oktie Hassanzadeh

  61. Learning Long- and Short-term Representations for Temporal Knowledge Graph Reasoning

    Mengqi Zhang, Yuwei Xia, Qiang Liu, Shu Wu, Liang Wang

  62. Meta-Learning Based Knowledge Extrapolation for Temporal Knowledge Graph

    Zhongwu Chen, Chengjin Xu, Fenglong Su, Zhen Huang, Yong Dou

  63. Heterogeneous Federated Knowledge Graph Embedding Learning and Unlearning

    Xiangrong Zhu, Guangyao Li, Wei Hu

  64. Can Persistent Homology provide an efficient alternative for Evaluation of Knowledge Graph Completion Methods

    Anson Bastos, Kuldeep Singh, Abhishek Nadgeri, Johannes Hoffart, Manish Singh, Toyotaro Suzumura

  65. Knowledge Graph Question Answering with Ambiguous Query

    Lihui Liu, Yuzhong Chen, Mahashweta Das, Hao Yang, Hanghang Tong

  66. Attribute-Consistent Knowledge Graph Representation Learning for Multi-Modal Entity Alignment

    Qian Li, Shu Guo, Yangyifei Luo, Cheng Ji, Lihong Wang, Jiawei Sheng, Jianxin Li

  67. Hierarchy-Aware Multi-Hop Question Answering over Knowledge Graphs

    Junnan Dong, Qinggang Zhang, Xiao Huang, Keyu Duan, Qiaoyu Tan, Zhimeng Jiang

  68. Unsupervised Entity Alignment for Temporal Knowledge Graphs

    Xiaoze Liu, Junyang Wu, Tianyi Li, Lu Chen, Yunjun Gao

  69. Hierarchical Self-Attention Embedding for Temporal Knowledge Graph Completion

    Xin Ren, Luyi Bai, Qianwen Xiao, Xiangxi Meng

  70. KRACL: Contrastive Learning with Graph Context Modeling for Sparse Knowledge Graph Completion

    Zhaoxuan Tan, Zilong Chen, Shangbin Feng, Qingyue Zhang, Qinghua Zheng, Jundong Li, Minnan Luo

  71. TRAVERS: A Diversity-Based Dynamic Approach to Iterative Relevance Search over Knowledge Graphs

    Ziyang Li, Yu Gu, Yulin Shen, Wei Hu, Gong Cheng

  72. Structure Pretraining and Prompt Tuning for Knowledge Graph Transfer

    Wen Zhang, Yushan Zhu, Mingyang Chen, Yuxia Geng, Yufeng Huang, Yajing Xu, Wenting Song, Huajun Chen

  73. TEA: Time-aware Entity Alignment in Knowledge Graphs

    Yu Liu, Wen Hua, Kexuan Xin, Saeid Hosseini, Xiaofang Zhou

  74. Link Prediction with Attention Applied on Multiple Knowledge Graph Embedding Models

    Cosimo Gregucci, Mojtaba Nayyeri, Daniel Hernández, Steffen Staab

  75. Knowledge Graph Completion with Counterfactual Augmentation

    Heng Chang, Jie Cai, Jia Li

  76. Mutually-paced Knowledge Distillation for Cross-lingual Temporal Knowledge Graph Reasoning

    Ruijie Wang, Zheng Li, Jingfeng Yang, Tianyu Cao, Chao Zhang, Bing Yin, Tarek F. Abdelzaher

  77. Message Function Search for Knowledge Graph Embedding

    Shimin Di, Lei Chen

  78. Detecting Socially Abnormal Highway Driving Behaviors via Recurrent Graph Attention Networks

    Yue Hu, Yuhang Zhang, Yanbing Wang, Daniel B. Work

  79. Bipartite Graph Convolutional Hashing for Effective and Efficient Top-N Search in Hamming Space

    Yankai Chen, Yixiang Fang, Yifei Zhang, Irwin King

  80. Fairness-Aware Clique-Preserving Spectral Clustering of Temporal Graphs

    Dongqi Fu, Dawei Zhou, Ross Maciejewski, Arie Croitoru, Marcus Boyd, Jingrui He

  81. PaGE-Link: Path-based Graph Neural Network Explanation for Heterogeneous Link Prediction

    Shichang Zhang, Jiani Zhang, Xiang Song, Soji Adeshina, Da Zheng, Christos Faloutsos, Yizhou Sun

  82. Learning to Simulate Crowd Trajectories with Graph Networks

    Hongzhi Shi, Quanming Yao, Yong Li

  1. Instant Representation Learning for Recommendation over Large Dynamic Graphs

    Cheng Wu (Tsinghua University); Chaokun Wang (Tsinghua University); Jingcao Xu (Tsinghua University); ZiWei Fang (Tsinghua University); Tiankai Gu (Alibaba Group); Changping Wang (Kuai shou); Yang Song (Kuaishou Inc); Kai Zheng (Kuaishou); Xiaowei Wang (Beijing Kuaishou Technology Co., Ltd.); Guorui Zhou (Kuaishou Inc)*

  2. MMKGR: Multi-hop Multi-modal Knowledge Graph Reasoning

    Shangfei Zheng (Soochow University); Weiqing Wang (Monash University); JIanfeng Qu (Soochow University); Hongzhi Yin (The University of Queensland); Wei Chen (Soochow University); Lei Zhao (Soochow University)*

  3. Relational Temporal Graph Convolutional Networks for Ranking-Based Stock Prediction

    Zetao Zheng (University of Electronic Science and Technology of China); Jie Shao (University of Electronic Science and Technology of China); Jia Zhu (Zhejiang Normal University); Heng Tao Shen (University of Electronic Science and Technology of China (UESTC))*

  4. TDB: Breaking All Hop-Constrained Cycles in Billion-Scale Directed Graphs

    You Peng (University of New South Wales); Xuemin Lin (University of New South Wales); Michael R Yu (UNSW); Wenjie Zhang (University of New South Wales); Lu Qin (UTS)*

  5. Disconnected Emerging Knowledge Graph Oriented Inductive Link Prediction

    Yufeng Zhang (Soochow University); Weiqing Wang (Monash University); Hongzhi Yin (The University of Queensland); Pengpeng Zhao (Soochow University); Wei Chen (Soochow University); Lei Zhao (Soochow University)*

  6. When Spatio-Temporal Meet Wavelets: Disentangled Traffic Forecasting via Efficient Spectral Graph Attention Networks

    Yuchen Fang (Beijing University of Posts and Telecommunications); Yanjun Qin (Beijing University of Posts and Telecommunications); Haiyong Luo (Research Center for Ubiquitous Computing Systems, Institute of Computing Technology, Chinese Academy of Sciences); Fang Zhao (School of Software Engineering, Beijing University of Posts and Telecommunications); Bingbing Xu ( Institute of Computing Technology,University of Chinese Academy of Sciences); Liang Zeng (Tsinghua University); Chenxing Wang (Beijing University of Posts and Telecommunications)*

  7. Jointly Attacking Graph Neural Network and its Explanations

    “Wenqi FAN (The Hong Kong Polytechnic University); Han Xu (Michigan State University); Wei Jin (Michigan State University); Xiaorui Liu (North Carolina State University); Xianfeng Tang (Amazon); Suhang Wang (Pennsylvania State University); Qing Li (The Hong Kong Polytechnic University); Jiliang Tang (Michigan State University); Jianping Wang (City University of Hong Kong); Charu Aggarwal (IBM)”*

  8. Revisiting Citation Prediction with Cluster-Aware Text-Enhanced Heterogeneous Graph Neural Networks

    Carl Yang (Emory University); Jiawei Han (UIUC)*

  9. CLDG: Contrastive Learning on Dynamic Graphs

    Yiming Xu (Xi’an Jiaotong University); Bin Shi (Xi’an jiaotong University); Teng Ma (Xi’an Jiaotong University); Bo Dong (Xi’an Jiaotong University); Haoyi Zhou (Beihang University); Qinghua Zheng (School of Electronic and Information Engineering, Xi’an Jiaotong University)*

  10. Relational Message Passing for Fully Inductive Knowledge Graph Completion

    Yuxia Geng (Zhejiang University); Jiaoyan Chen (The University of Manchester); Jeff Z. Pan (The University of Edinburgh); Mingyang Chen (Zhejiang University); Song Jiang (Huawei Technologies Co., Ltd); Wen Zhang (Zhejiang University); Huajun Chen (Zhejiang University)*

  11. Layer-refined Graph Convolutional Networks for Recommendation

    Xin Zhou (Nanyang Technological University); Donghui Lin (Okayama University); Yong Liu (Nanyang Technological University); Chunyan Miao (NTU)*

  12. A Generic Reinforced Explainable Framework with Knowledge Graph for Session-based Recommendation

    Huizi Wu (Shanghai University of Finance and Economics); Hui Fang (Shanghai University of Finance and Economics); Zhu Sun (ASTAR); Cong Geng (Shanghai University of Finance and Economics); Xinyu Kong (Ant Group); Yew Soon Ong (Nanyang Technological University, Nanyang View, Singapore)

  13. HyGNN: Drug-Drug Interaction Prediction via Hypergraph Neural Network

    Khaled Mohammed Saifuddin (Georgia State University); Briana Bumgardner (Rice University); Farhan Tanvir (Oklahoma State University); Esra Akbas (Georgia State University)*

  14. Demystifying Bitcoin Address Behavior via Graph Neural Networks

    Zhengjie Huang (Zhejiang University); Yunyang Huang (UESTC); Peng Qian (Zhejiang University); Jianhai Chen (Zhejiang University); Qinming He (Zhejiang University)*

  15. RETIA: Relation-Entity Twin-Interact Aggregation for Temporal Knowledge Graph Extrapolation

    Kangzheng Liu (Huazhong University of Science and Technology); Feng Zhao (Huazhong University of Science and Technology); Guandong Xu (University of Technology Sydney, Australia); Xianzhi Wang (University of Technology Sydney); Hai Jin (Huazhong University of Science and Technology)*

  16. Air-Ground Spatial Crowdsourcing with UAV Carriers by Geometric Graph Convolutional Multi-Agent Deep Reinforcement Learning

    Yu Wang (Beijing Institute of Technology); Jingfei Wu (Beijing Institute of Technology); Hua Xingyuan (School of Computer Science Beijing Institute of Technology); Chi Harold Liu (Beijing Institute of Technology); Guozheng Li (Beijing Institute of Technology); Jianxin Zhao (Beijing Institute of Technology); Ye Yuan ( Beijing Institute of Technology); Guoren Wang (Beijing Institute of Technology)*

  17. Dynamic Hypergraph Structure Learning for Traffic Flow Forecasting

    Yusheng Zhao (Peking University); Xiao Luo (UCLA); Wei Ju (Peking University); Chong Chen (Peking University); Xian-Sheng Hua (Terminus Group); Ming Zhang (Peking University)*

  18. Disentangled Graph Social Recommendation

    Lianghao Xia (University of Hong Kong); Yizhen Shao (South China University of Technology); Chao Huang (University of Hong Kong); Yong Xu (South China University of Technology); Huance Xu (South China University of Technology); Jian Pei (Simon Fraser University)*

  19. Fast Unsupervised Graph Embedding via Graph Zoom Learning

    Ziyang Liu (Tsinghua University); Chaokun Wang (Tsinghua University); Yunkai Lou (Tsinghua University); Hao Feng (Tsinghua University)*

  20. AutoAC: Towards Automated Attribute Completion for Heterogeneous Graph Neural Network

    Guanghui Zhu (Nanjing University); zhu zhennan (Nanjing University); Wenjie Wang (Nanjing University); Zhuoer Xu (Nanjing University); Chunfeng Yuan (Nanjing University); Yihua Huang (Nanjing University)*

  21. Multimodal Biological Knowledge Graph Completion via Triple Co-attention Mechanism

    Derong Xu (University of Science and Technology of China); jingbo zhou (Baidu Research); Tong Xu (University of Science and Technology of China); yuan xia (baidu); Ji Liu (Baidu Research); Enhong Chen (University of Science and Technology of China); Dejing Dou (Baidu)*

  22. SEIGN: A Simple and Efficient Graph Neural Network for Large Dynamic Graphs

    Xiao Qin (AWS AI/ML); Nasrullah Sheikh (IBM); Chuan Lei (Amazon Web Services); Berthold Reinwald (IBM Research-Almaden); Giacomo Domeniconi (U.S. Bank)*

  1. Spatio-Temporal Denoising Graph Autoencoders with Data Augmentation for Photovoltaic Data Imputation

    Yangxin Fan (Case Western Reserve University); Xuanji Yu (Case Western Reserve University); Raymond Wieser (Case Western Reserve University); David Meakin (SunPower Corporation); Avishai Shaton (SolarEdge Technologies); Jean-Nicolas Jaubert (CSI Solar Co.Ltd.); Robert Flottemesch (Brookfield Renewable U.S.); Michael Howell (C2 Energy Capital); Jennifer Braid (Sandia National Labs); Laura Bruckman (Case Western Reserve University); Roger H French (Case Western Reserve University); Yinghui Wu (Case Western Reserve University)*

  2. Caerus: A Caching-based Framework for Scalable Temporal Graph Neural Networks

    Yiming Li (Hong Kong University of Science and Technology); Yanyan Shen (Shanghai Jiao Tong University); Lei Chen (Hong Kong University of Science and Technology); Mingxuan Yuan (Huawei)*

  3. Scalable and Efficient Full-Graph GNN Training for Large Graphs

    Xinchen Wan (HKUST); Kaiqiang Xu (HKUST); Xudong Liao (HKUST); Yilun Jin (The Hong Kong University of Science and Technology); Kai Chen (HKUST); Xin Jin (Peking University)

  4. EARLY: Efficient and Reliable Graph Neural Network for Dynamic Graphs

    Haoyang Li (The Hong Kong University of Science and Technology); Lei Chen (Hong Kong University of Science and Technology);

  5. DUCATI: A Dual-Cache Training System for Graph Neural Networks on Giant Graphs with GPU

    Xin Zhang (Hong Kong University of Science and Technology); Yanyan Shen (Shanghai Jiao Tong University); Yingxia Shao (BUPT); Lei Chen (Hong Kong University of Science and Technology)

  1. Detecting Out-Of-Context Objects Using Graph Contextual Reasoning Network

    Manoj Acharya, Anirban Roy, Kaushik Koneripalli, Susmit Jha, Christopher Kanan, Ajay Divakaran

  2. Cluster Attack: Query-based Adversarial Attacks on Graph with Graph-Dependent Priors

    Zhengyi Wang, Zhongkai Hao, Ziqiao Wang, Hang Su, Jun Zhu

  3. Learning Graph-based Residual Aggregation Network for Group Activity Recognition

    Wei Li, Tianzhao Yang, Xiao Wu, Zhaoquan Yuan

  4. Hypertron: Explicit Social-Temporal Hypergraph Framework for Multi-Agent Forecasting

    Yu Tian, Xingliang Huang, Ruigang Niu, Hongfeng Yu, Peijin Wang, Xian Sun

  5. Eliminating Backdoor Triggers for Deep Neural Networks Using Attention Relation Graph Distillation

    Jun Xia, Ting Wang, Jiepin Ding, Xian Wei, Mingsong Chen

  6. Using Constraint Programming and Graph Representation Learning for Generating Interpretable Cloud Security Policies

    Mikhail Kazdagli, Mohit Tiwari, Akshat Kumar

  7. Hypergraph Structure Learning for Hypergraph Neural Networks

    Derun Cai, Moxian Song, Chenxi Sun, Baofeng Zhang, Shenda Hong, Hongyan Li

  8. Entity Alignment with Reliable Path Reasoning and Relation-aware Heterogeneous Graph Transformer

    Weishan Cai, Wenjun Ma, Jieyu Zhan, Yuncheng Jiang

  9. Can Abnormality be Detected by Graph Neural Networks

    Ziwei Chai, Siqi You, Yang Yang, Shiliang Pu, Jiarong Xu, Haoyang Cai, Weihao Jiang

  10. Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification

    Chaochao Chen, Jun Zhou, Longfei Zheng, Huiwen Wu, Lingjuan Lyu, Jia Wu, Bingzhe Wu, Ziqi Liu, Li Wang, Xiaolin Zheng

  11. Filtration-Enhanced Graph Transformation

    Zijian Chen, Rong-Hua Li, Hongchao Qin, Huanzhong Duan, Yanxiong Lu, Qiangqiang Dai, Guoren Wang

  12. Modeling Precursors for Temporal Knowledge Graph Reasoning via Auto-encoder Structure

    Yifu Gao, Linhui Feng, Zhigang Kan, Yi Han, Linbo Qiao, Dongsheng Li

  13. Self-supervised Graph Neural Networks for Multi-behavior Recommendation

    Shuyun Gu, Xiao Wang, Chuan Shi, Ding Xiao

  14. MERIT: Learning Multi-level Representations on Temporal Graphs

    Binbin Hu, Zhengwei Wu, Jun Zhou, Ziqi Liu, Zhigang Huangfu, Zhiqiang Zhang, Chaochao Chen

  15. GraphDIVE: Graph Classification by Mixture of Diverse Experts

    Fenyu Hu, Liping Wang, Qiang Liu, Shu Wu, Liang Wang, Tieniu Tan

  16. A Sparse-Motif Ensemble Graph Convolutional Network against Over-smoothing

    Xuan Jiang, Zhiyong Yang, Peisong Wen, Li Su, Qingming Huang

  17. CGMN: A Contrastive Graph Matching Network for Self-Supervised Graph Similarity Learning

    Di Jin, Luzhi Wang, Yizhen Zheng, Xiang Li, Fei Jiang, Wei Lin, Shirui Pan

  18. RAW-GNN: RAndom Walk Aggregation based Graph Neural Network

    Di Jin, Rui Wang, Meng Ge, Dongxiao He, Xiang Li, Wei Lin, Weixiong Zhang

  19. Gromov-Wasserstein Discrepancy with Local Differential Privacy for Distributed Structural Graphs

    Hongwei Jin, Xun Chen

  20. TGNN: A Joint Semi-supervised Framework for Graph-level Classification

    Wei Ju, Xiao Luo, Meng Qu, Yifan Wang, Chong Chen, Minghua Deng, Xian-Sheng Hua, Ming Zhang

  21. TiRGN: Time-Guided Recurrent Graph Network with Local-Global Historical Patterns for Temporal Knowledge Graph Reasoning

    Yujia Li, Shiliang Sun, Jing Zhao

  22. Raising the Bar in Graph-level Anomaly Detection

    Chen Qiu, Marius Kloft, Stephan Mandt, Maja Rudolph

  23. Long-term Spatio-Temporal Forecasting via Dynamic Multiple-Graph Attention

    Wei Shao, Zhiling Jin, Shuo Wang, Yufan Kang, Xiao Xiao, Hamid Menouar, Zhaofeng Zhang, Junshan Zhang, Flora D. Salim

  24. Beyond Homophily: Structure-aware Path Aggregation Graph Neural Network

    Yifei Sun, Haoran Deng, Yang Yang, Chunping Wang, Jiarong Xu, Renhong Huang, Linfeng Cao, Yang Wang, Lei Chen

  25. Positive-Unlabeled Learning with Adversarial Data Augmentation for Knowledge Graph Completion

    Zhenwei Tang, Shichao Pei, Zhao Zhang, Yongchun Zhu, Fuzhen Zhuang, Robert Hoehndorf, Xiangliang Zhang

  26. Augmenting Knowledge Graphs for Better Link Prediction

    Jiang Wang, Filip Ilievski, Pedro A. Szekely, Ke-Thia Yao

  27. FAITH: Few-Shot Graph Classification with Hierarchical Task Graphs

    Song Wang, Yushun Dong, Xiao Huang, Chen Chen, Jundong Li

  28. Ensemble Multi-Relational Graph Neural Networks

    Yuling Wang, Hao Xu, Yanhua Yu, Mengdi Zhang, Zhenhao Li, Yuji Yang, Wei Wu

  29. Multi-Graph Fusion Networks for Urban Region Embedding

    Shangbin Wu, Xu Yan, Xiaoliang Fan, Shirui Pan, Shichao Zhu, Chuanpan Zheng, Ming Cheng, Cheng Wang

  30. Subgraph Neighboring Relations Infomax for Inductive Link Prediction on Knowledge Graphs

    Xiaohan Xu, Peng Zhang, Yongquan He, Chengpeng Chao, Chaoyang Yan

  31. Regularized Graph Structure Learning with Semantic Knowledge for Multi-variates Time-Series Forecasting

    Hongyuan Yu, Ting Li, Weichen Yu, Jianguo Li, Yan Huang, Liang Wang, Alex X. Liu

  32. Dynamic Graph Learning Based on Hierarchical Memory for Origin-Destination Demand Prediction

    Ruixing Zhang, Liangzhe Han, Boyi Liu, Jiayuan Zeng, Leilei Sun

  33. GRELEN: Multivariate Time Series Anomaly Detection from the Perspective of Graph Relational Learning

    Weiqi Zhang, Chen Zhang, Fugee Tsung

  34. Enhancing Sequential Recommendation with Graph Contrastive Learning

    Yixin Zhang, Yong Liu, Yonghui Xu, Hao Xiong, Chenyi Lei, Wei He, Lizhen Cui, Chunyan Miao

  35. Table2Graph: Transforming Tabular Data to Unified Weighted Graph

    Kaixiong Zhou, Zirui Liu, Rui Chen, Li Li, Soo-Hyun Choi, Xia Hu

  36. Spiking Graph Convolutional Networks

    Zulun Zhu, Jiaying Peng, Jintang Li, Liang Chen, Qi Yu, Siqiang Luo

  37. Data-Free Adversarial Knowledge Distillation for Graph Neural Networks

    Yuanxin Zhuang, Lingjuan Lyu, Chuan Shi, Carl Yang, Lichao Sun

  38. Proximity Enhanced Graph Neural Networks with Channel Contrast

    Wei Zhuo, Guang Tan

  39. Personalized Federated Learning With a Graph

    Fengwen Chen, Guodong Long, Zonghan Wu, Tianyi Zhou, Jing Jiang

  40. Adversarial Explanations for Knowledge Graph Embeddings

    Patrick Betz, Christian Meilicke, Heiner Stuckenschmidt

  41. Multi-view Unsupervised Graph Representation Learning

    Jiangzhang Gan, Rongyao Hu, Mengmeng Zhan, Yujie Mo, Yingying Wan, Xiaofeng Zhu

  42. Bootstrapping Informative Graph Augmentation via A Meta Learning Approach

    Hang Gao, Jiangmeng Li, Wenwen Qiang, Lingyu Si, Fuchun Sun, Changwen Zheng

  43. Attributed Graph Clustering with Dual Redundancy Reduction

    Lei Gong, Sihang Zhou, Wenxuan Tu, Xinwang Liu

  44. Learning Continuous Graph Structure with Bilevel Programming for Graph Neural Networks

    Minyang Hu, Hong Chang, Bingpeng Ma, Shiguang Shan

  45. Type-aware Embeddings for Multi-Hop Reasoning over Knowledge Graphs

    Zhiwei Hu, Víctor Gutiérrez-Basulto, Zhiliang Xiang, Xiaoli Li, Ru Li, Jeff Z. Pan

  46. On the Channel Pruning using Graph Convolution Network for Convolutional Neural Network Acceleration

    Di Jiang, Yuan Cao, Qiang Yang

  47. Graph Masked Autoencoder Enhanced Predictor for Neural Architecture Search

    Kun Jing, Jungang Xu, Pengfei Li

  48. DyGRAIN: An Incremental Learning Framework for Dynamic Graphs

    Seoyoon Kim, Seongjun Yun, Jaewoo Kang

  49. SGAT: Simplicial Graph Attention Network

    See Hian Lee, Feng Ji, Wee Peng Tay

  50. Rethinking the Setting of Semi-supervised Learning on Graphs

    Ziang Li, Ming Ding, Weikai Li, Zihan Wang, Ziyu Zeng, Yukuo Cen, Jie Tang

  51. Deep Graph Matching for Partial Label Learning

    Gengyu Lyu, Yanan Wu, Songhe Feng

  52. Escaping Feature Twist: A Variational Graph Auto-Encoder for Node Clustering

    Nairouz Mrabah, Mohamed Bouguessa, Riadh Ksantini

  53. RecipeRec: A Heterogeneous Graph Learning Model for Recipe Recommendation

    Yijun Tian, Chuxu Zhang, Zhichun Guo, Chao Huang, Ronald A. Metoyer, Nitesh V. Chawla

  54. Recipe2Vec: Multi-modal Recipe Representation Learning with Graph Neural Networks

    Yijun Tian, Chuxu Zhang, Zhichun Guo, Yihong Ma, Ronald A. Metoyer, Nitesh V. Chawla

  55. Initializing Then Refining: A Simple Graph Attribute Imputation Network

    Wenxuan Tu, Sihang Zhou, Xinwang Liu, Yue Liu, Zhiping Cai, En Zhu, Changwang Zhang, Jieren Cheng

  56. EMGC²F: Efficient Multi-view Graph Clustering with Comprehensive Fusion

    Danyang Wu, Jitao Lu, Feiping Nie, Rong Wang, Yuan Yuan

  57. A Simple yet Effective Method for Graph Classification

    Junran Wu, Shangzhe Li, Jianhao Li, Yicheng Pan, Ke Xu

  58. Stabilizing and Enhancing Link Prediction through Deepened Graph Auto-Encoders

    Xinxing Wu, Qiang Cheng

  59. Information Augmentation for Few-shot Node Classification

    Zongqian Wu, Peng Zhou, Guoqiu Wen, Yingying Wan, Junbo Ma, Debo Cheng, Xiaofeng Zhu

  60. Online ECG Emotion Recognition for Unknown Subjects via Hypergraph-Based Transfer Learning

    Yalan Ye, Tongjie Pan, Qianhe Meng, Jingjing Li, Li Lu

  61. Fine-Tuning Graph Neural Networks via Graph Topology Induced Optimal Transport

    Jiying Zhang, Xi Xiao, Long-Kai Huang, Yu Rong, Yatao Bian

  62. Hierarchical Diffusion Scattering Graph Neural Network

    Ke Zhang, Xinyan Pu, Jiaxing Li, Jiasong Wu, Huazhong Shu, Youyong Kong

  63. RoSA: A Robust Self-Aligned Framework for Node-Node Graph Contrastive Learning

    Yun Zhu, Jianhao Guo, Fei Wu, Siliang Tang

  64. Subsequence-based Graph Routing Network for Capturing Multiple Risk Propagation Processes

    Rui Cheng, Qing Li

  65. Monolith to Microservices: Representing Application Software through Heterogeneous Graph Neural Network

    Alex Mathai, Sambaran Bandyopadhyay, Utkarsh Desai, Srikanth Tamilselvam

  66. Communicative Subgraph Representation Learning for Multi-Relational Inductive Drug-Gene Interaction Prediction

    Jiahua Rao, Shuangjia Zheng, Sijie Mai, Yuedong Yang

  67. FOGS: First-Order Gradient Supervision with Learning-based Graph for Traffic Flow Forecasting

    Xuan Rao, Hao Wang, Liang Zhang, Jing Li, Shuo Shang, Peng Han

  68. Effective Graph Context Representation for Document-level Machine Translation

    Kehai Chen, Muyun Yang, Masao Utiyama, Eiichiro Sumita, Rui Wang, Min Zhang

  69. Interactive Information Extraction by Semantic Information Graph

    Siqi Fan, Yequan Wang, Jing Li, Zheng Zhang, Shuo Shang, Peng Han

  70. Control Globally, Understand Locally: A Global-to-Local Hierarchical Graph Network for Emotional Support Conversation

    Wei Peng, Yue Hu, Luxi Xing, Yuqiang Xie, Yajing Sun, Yunpeng Li

  71. Neural Subgraph Explorer: Reducing Noisy Information via Target-oriented Syntax Graph Pruning

    Bowen Xing, Ivor W. Tsang

  72. Contrastive Graph Transformer Network for Personality Detection

    Yangfu Zhu, Linmei Hu, Xinkai Ge, Wanrong Peng, Bin Wu

  73. Dynamic Structure Learning through Graph Neural Network for Forecasting Soil Moisture in Precision Agriculture

    Anoushka Vyas, Sambaran Bandyopadhyay

  74. Survey on Graph Neural Network Acceleration: An Algorithmic Perspective

    Xin Liu, Mingyu Yan, Lei Deng, Guoqi Li, Xiaochun Ye, Dongrui Fan, Shirui Pan, Yuan Xie

  1. Learning to Predict Graphs with Fused Gromov-Wasserstein Barycenters

    Luc Brogat-Motte, Rémi Flamary, Céline Brouard, Juho Rousu, Florence d'Alché-Buc

  2. Convergence of Invariant Graph Networks

    Chen Cai, Yusu Wang

  3. Structure-Aware Transformer for Graph Representation Learning

    Dexiong Chen, Leslie O'Bray, Karsten M. Borgwardt

  4. Faster Fundamental Graph Algorithms via Learned Predictions

    Justin Y. Chen, Sandeep Silwal, Ali Vakilian, Fred Zhang

  5. Deep Variational Graph Convolutional Recurrent Network for Multivariate Time Series Anomaly Detection

    Wenchao Chen, Long Tian, Bo Chen, Liang Dai, Zhibin Duan, Mingyuan Zhou

  6. Optimization-Induced Graph Implicit Nonlinear Diffusion

    Qi Chen, Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin

  7. From block-Toeplitz matrices to differential equations on graphs: towards a general theory for scalable masked Transformers

    Krzysztof Choromanski, Han Lin, Haoxian Chen, Tianyi Zhang, Arijit Sehanobish, Valerii Likhosherstov, Jack Parker-Holder, Tamás Sarlós, Adrian Weller, Thomas Weingarten

  8. PACE: A Parallelizable Computation Encoder for Directed Acyclic Graphs

    Zehao Dong, Muhan Zhang, Fuhai Li, Yixin Chen

  9. SE(3) Equivariant Graph Neural Networks with Complete Local Frames

    Weitao Du, He Zhang, Yuanqi Du, Qi Meng, Wei Chen, Nanning Zheng, Bin Shao, Tie-Yan Liu

  10. pathGCN: Learning General Graph Spatial Operators from Paths

    Moshe Eliasof, Eldad Haber, Eran Treister

  11. p-Laplacian Based Graph Neural Networks

    Guoji Fu, Peilin Zhao, Yatao Bian

  12. On the Equivalence Between Temporal and Static Equivariant Graph Representations

    Jianfei Gao, Bruno Ribeiro

  13. Large-Scale Graph Neural Architecture Search

    Chaoyu Guan, Xin Wang, Hong Chen, Ziwei Zhang, Wenwu Zhu

  14. Understanding and Improving Knowledge Graph Embedding for Entity Alignment

    Lingbing Guo, Qiang Zhang, Zequn Sun, Mingyang Chen, Wei Hu, Huajun Chen

  15. G-Mixup: Graph Data Augmentation for Graph Classification

    Xiaotian Han, Zhimeng Jiang, Ninghao Liu, Xia Hu

  16. GNNRank: Learning Global Rankings from Pairwise Comparisons via Directed Graph Neural Networks

    Yixuan He, Quan Gan, David Wipf, Gesine D. Reinert, Junchi Yan, Mihai Cucuringu

  17. Going Deeper into Permutation-Sensitive Graph Neural Networks

    Zhongyu Huang, Yingheng Wang, Chaozhuo Li, Huiguang He

  18. LeNSE: Learning To Navigate Subgraph Embeddings for Large-Scale Combinatorial Optimisation

    David Ireland, Giovanni Montana

  19. Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations

    Jaehyeong Jo, Seul Lee, Sung Ju Hwang

  20. Comprehensive Analysis of Negative Sampling in Knowledge Graph Representation Learning

    Hidetaka Kamigaito, Katsuhiko Hayashi

  21. Simultaneous Graph Signal Clustering and Graph Learning

    Abdullah Karaaslanli, Selin Aviyente

  22. DSTAGNN: Dynamic Spatial-Temporal Aware Graph Neural Network for Traffic Flow Forecasting

    Shiyong Lan, Yitong Ma, Weikang Huang, Wenwu Wang, Hongyu Yang, Pyang Li

  23. G2CN: Graph Gaussian Convolution Networks with Concentrated Graph Filters

    Mingjie Li, Xiaojun Guo, Yifei Wang, Yisen Wang, Zhouchen Lin

  24. Generalization Guarantee of Training Graph Convolutional Networks with Graph Topology Sampling

    Hongkang Li, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong

  25. Let Invariant Rationale Discovery Inspire Graph Contrastive Learning

    Sihang Li, Xiang Wang, An Zhang, Yingxin Wu, Xiangnan He, Tat-Seng Chua

  26. HousE: Knowledge Graph Embedding with Householder Parameterization

    Rui Li, Jianan Zhao, Chaozhuo Li, Di He, Yiqi Wang, Yuming Liu, Hao Sun, Senzhang Wang, Weiwei Deng, Yanming Shen, Xing Xie, Qi Zhang

  27. Finding Global Homophily in Graph Neural Networks When Meeting Heterophily

    Xiang Li, Renyu Zhu, Yao Cheng, Caihua Shan, Siqiang Luo, Dongsheng Li, Weining Qian

  28. Boosting Graph Structure Learning with Dummy Nodes

    Xin Liu, Jiayang Cheng, Yangqiu Song, Xin Jiang

  29. Local Augmentation for Graph Neural Networks

    Songtao Liu, Rex Ying, Hanze Dong, Lanqing Li, Tingyang Xu, Yu Rong, Peilin Zhao, Junzhou Huang, Dinghao Wu

  30. SPECTRE: Spectral Conditioning Helps to Overcome the Expressivity Limits of One-shot Graph Generators

    Karolis Martinkus, Andreas Loukas, Nathanaël Perraudin, Roger Wattenhofer

  31. Interpretable and Generalizable Graph Learning via Stochastic Attention Mechanism

    Siqi Miao, Mia Liu, Pan Li

  32. SpeqNets: Sparsity-aware permutation-equivariant graph networks

    Christopher Morris, Gaurav Rattan, Sandra Kiefer, Siamak Ravanbakhsh

  33. A Theoretical Comparison of Graph Neural Network Extensions

    Pál András Papp, Roger Wattenhofer

  34. Nonlinear Feature Diffusion on Hypergraphs

    Konstantin Prokopchik, Austin R. Benson, Francesco Tudisco

  35. Graph Neural Architecture Search Under Distribution Shifts

    Yijian Qin, Xin Wang, Ziwei Zhang, Pengtao Xie, Wenwu Zhu

  36. Graph-Coupled Oscillator Networks

    T. Konstantin Rusch, Ben Chamberlain, James Rowbottom, Siddhartha Mishra, Michael M. Bronstein

  37. Rethinking Graph Neural Networks for Anomaly Detection

    Jianheng Tang, Jiajin Li, Ziqi Gao, Jia Li

  38. Cross-Space Active Learning on Graph Convolutional Networks

    Yufei Tao, Hao Wu, Shiyuan Deng

  39. What Dense Graph Do You Need for Self-Attention

    Yuxin Wang, Chu-Tak Lee, Qipeng Guo, Zhangyue Yin, Yunhua Zhou, Xuanjing Huang, Xipeng Qiu

  40. How Powerful are Spectral Graph Neural Networks

    Xiyuan Wang, Muhan Zhang

  41. Structural Entropy Guided Graph Hierarchical Pooling

    Junran Wu, Xueyuan Chen, Ke Xu, Shangzhe Li

  42. ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning

    Jun Xia, Lirong Wu, Ge Wang, Jintao Chen, Stan Z. Li

  43. Self-Supervised Representation Learning via Latent Graph Prediction

    Yaochen Xie, Zhao Xu, Shuiwang Ji

  44. Efficient Computation of Higher-Order Subgraph Attribution via Message Passing

    Ping Xiong, Thomas Schnake, Grégoire Montavon, Klaus-Robert Müller, Shinichi Nakajima

  45. Omni-Granular Ego-Semantic Propagation for Self-Supervised Graph Representation Learning

    Ling Yang, Shenda Hong

  46. A New Perspective on the Effects of Spectrum in Graph Neural Networks

    Mingqi Yang, Yanming Shen, Rui Li, Heng Qi, Qiang Zhang, Baocai Yin

  47. Molecular Representation Learning via Heterogeneous Motif Graph Neural Networks

    Zhaoning Yu, Hongyang Gao

  48. GraphFM: Improving Large-Scale GNN Training via Feature Momentum

    Haiyang Yu, Limei Wang, Bokun Wang, Meng Liu, Tianbao Yang, Shuiwang Ji

  49. Deep and Flexible Graph Neural Architecture Search

    Wentao Zhang, Zheyu Lin, Yu Shen, Yang Li, Zhi Yang, Bin Cui

  50. NAFS: A Simple yet Tough-to-beat Baseline for Graph Representation Learning

    Wentao Zhang, Zeang Sheng, Mingyu Yang, Yang Li, Yu Shen, Zhi Yang, Bin Cui

  51. Learning to Solve PDE-constrained Inverse Problems with Graph Networks

    Qingqing Zhao, David B. Lindell, Gordon Wetzstein

  52. Neural-Symbolic Models for Logical Queries on Knowledge Graphs

    Zhaocheng Zhu, Mikhail Galkin, Zuobai Zhang, Jian Tang

  1. Motif Prediction with Graph Neural Networks

    Maciej Besta, Raphael Grob, Cesare Miglioli, Nicola Bernold, Grzegorz Kwasniewski, Gabriel Gjini, Raghavendra Kanakagiri, Saleh Ashkboos, Lukas Gianinazzi, Nikoli Dryden, Torsten Hoefler

  2. Efficient Join Order Selection Learning with Graph-based Representation

    Jin Chen, Guanyu Ye, Yan Zhao, Shuncheng Liu, Liwei Deng, Xu Chen, Rui Zhou, Kai Zheng

  3. Learning Binarized Graph Representations with Multi-faceted Quantization Reinforcement for Top-K Recommendation

    Yankai Chen, Huifeng Guo, Yingxue Zhang, Chen Ma, Ruiming Tang, Jingjie Li, Irwin King

  4. On Structural Explanation of Bias in Graph Neural Networks

    Yushun Dong, Song Wang, Yu Wang, Tyler Derr, Jundong Li

  5. FreeKD: Free-direction Knowledge Distillation for Graph Neural Networks

    Kaituo Feng, Changsheng Li, Ye Yuan, Guoren Wang

  6. Meta-Learned Metrics over Multi-Evolution Temporal Graphs

    Dongqi Fu, Liri Fang, Ross Maciejewski, Vetle I. Torvik, Jingrui He

  7. Subset Node Anomaly Tracking over Large Dynamic Graphs

    Xingzhi Guo, Baojian Zhou, Steven Skiena

  8. Continuous-Time and Multi-Level Graph Representation Learning for Origin-Destination Demand Prediction

    Liangzhe Han, Xiaojian Ma, Leilei Sun, Bowen Du, Yanjie Fu, Weifeng Lv, Hui Xiong

  9. Compressing Deep Graph Neural Networks via Adversarial Knowledge Distillation

    Huarui He, Jie Wang, Zhanqiu Zhang, Feng Wu

  10. GraphMAE: Self-Supervised Masked Graph Autoencoders

    Zhenyu Hou, Xiao Liu, Yukuo Cen, Yuxiao Dong, Hongxia Yang, Chunjie Wang, Jie Tang

  11. Global Self-Attention as a Replacement for Graph Convolution

    Md. Shamim Hussain, Mohammed J. Zaki, Dharmashankar Subramanian

  12. Dual-Geometric Space Embedding Model for Two-View Knowledge Graphs

    Roshni G. Iyer, Yunsheng Bai, Wei Wang, Yizhou Sun

  13. Detecting Cash-out Users via Dense Subgraphs

    Yingsheng Ji, Zheng Zhang, Xinlei Tang, Jiachen Shen, Xi Zhang, Guangwen Yang

  14. A Spectral Representation of Networks: The Path of Subgraphs

    Shengmin Jin, Hao Tian, Jiayu Li, Reza Zafarani

  15. Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective

    Wei Jin, Xiaorui Liu, Yao Ma, Charu C. Aggarwal, Jiliang Tang

  16. Condensing Graphs via One-Step Gradient Matching

    Wei Jin, Xianfeng Tang, Haoming Jiang, Zheng Li, Danqing Zhang, Jiliang Tang, Bing Yin

  17. JuryGCN: Quantifying Jackknife Uncertainty on Graph Convolutional Networks

    Jian Kang, Qinghai Zhou, Hanghang Tong

  18. CoRGi: Content-Rich Graph Neural Networks with Attention

    Jooyeon Kim, Angus Lamb, Simon Woodhead, Simon Peyton Jones, Cheng Zhang, Miltiadis Allamanis

  19. FlowGEN: A Generative Model for Flow Graphs

    Furkan Kocayusufoglu, Arlei Silva, Ambuj K. Singh

  20. Variational Inference for Training Graph Neural Networks in Low-Data Regime through Joint Structure-Label Estimation

    Danning Lao, Xinyu Yang, Qitian Wu, Junchi Yan

  21. KPGT: Knowledge-Guided Pre-training of Graph Transformer for Molecular Property Prediction

    Han Li, Dan Zhao, Jianyang Zeng

  22. Domain Adaptation in Physical Systems via Graph Kernel

    Haoran Li, Hanghang Tong, Yang Weng

  23. Mining Spatio-Temporal Relations via Self-Paced Graph Contrastive Learning

    Rongfan Li, Ting Zhong, Xinke Jiang, Goce Trajcevski, Jin Wu, Fan Zhou

  24. Graph Structural Attack by Perturbing Spectral Distance

    Lu Lin, Ethan Blaser, Hongning Wang

  25. Source Localization of Graph Diffusion via Variational Autoencoders for Graph Inverse Problems

    Chen Ling, Junji Jiang, Junxiang Wang, Liang Zhao

  26. User-Event Graph Embedding Learning for Context-Aware Recommendation

    Dugang Liu, Mingkai He, Jinwei Luo, Jiangxu Lin, Meng Wang, Xiaolian Zhang, Weike Pan, Zhong Ming

  27. Graph-in-Graph Network for Automatic Gene Ontology Description Generation

    Fenglin Liu, Bang Yang, Chenyu You, Xian Wu, Shen Ge, Adelaide Woicik, Sheng Wang

  28. Joint Knowledge Graph Completion and Question Answering

    Lihui Liu, Boxin Du, Jiejun Xu, Yinglong Xia, Hanghang Tong

  29. RL2: A Call for Simultaneous Representation Learning and Rule Learning for Graph Streams

    Qu Liu, Tingjian Ge

  30. Mask and Reason: Pre-Training Knowledge Graph Transformers for Complex Logical Queries

    Xiao Liu, Shiyu Zhao, Kai Su, Yukuo Cen, Jiezhong Qiu, Mengdi Zhang, Wei Wu, Yuxiao Dong, Jie Tang

  31. UD-GNN: Uncertainty-aware Debiased Training on Semi-Homophilous Graphs

    Yang Liu, Xiang Ao, Fuli Feng, Qing He

  32. Geometer: Graph Few-Shot Class-Incremental Learning via Prototype Representation

    Bin Lu, Xiaoying Gan, Lina Yang, Weinan Zhang, Luoyi Fu, Xinbing Wang

  33. Spatio-Temporal Graph Few-Shot Learning with Cross-City Knowledge Transfer

    Bin Lu, Xiaoying Gan, Weinan Zhang, Huaxiu Yao, Luoyi Fu, Xinbing Wang

  34. Learning Causal Effects on Hypergraphs

    Jing Ma, Mengting Wan, Longqi Yang, Jundong Li, Brent J. Hecht, Jaime Teevan

  35. Evaluating Knowledge Graph Accuracy Powered by Optimized Human-machine Collaboration

    Yifan Qi, Weiguo Zheng, Liang Hong, Lei Zou

  36. Rep2Vec: Repository Embedding via Heterogeneous Graph Adversarial Contrastive Learning

    Yiyue Qian, Yiming Zhang, Qianlong Wen, Yanfang Ye, Chuxu Zhang

  37. Graph-Flashback Network for Next Location Recommendation

    Xuan Rao, Lisi Chen, Yong Liu, Shuo Shang, Bin Yao, Peng Han

  38. SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs

    Hongyu Ren, Hanjun Dai, Bo Dai, Xinyun Chen, Denny Zhou, Jure Leskovec, Dale Schuurmans

  39. Pre-training Enhanced Spatial-temporal Graph Neural Network for Multivariate Time Series Forecasting

    Zezhi Shao, Zhao Zhang, Fei Wang, Yongjun Xu

  40. GUIDE: Group Equality Informed Individual Fairness in Graph Neural Networks

    Weihao Song, Yushun Dong, Ninghao Liu, Jundong Li

  41. Learning on Graphs with Out-of-Distribution Nodes

    Yu Song, Donglin Wang

  42. Towards an Optimal Asymmetric Graph Structure for Robust Semi-supervised Node Classification

    Zixing Song, Yifei Zhang, Irwin King

  43. Causal Attention for Interpretable and Generalizable Graph Classification

    Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, Xiangnan He, Tat-Seng Chua

  44. GPPT: Graph Pre-training and Prompt Tuning to Generalize Graph Neural Networks

    Mingchen Sun, Kaixiong Zhou, Xin He, Ying Wang, Xin Wang

  45. Streaming Graph Neural Networks with Generative Replay

    Junshan Wang, Wenhao Zhu, Guojie Song, Liang Wang

  46. Improving Fairness in Graph Neural Networks via Mitigating Sensitive Attribute Leakage

    Yu Wang, Yuying Zhao, Yushun Dong, Huiyuan Chen, Jundong Li, Tyler Derr

  47. Graph Neural Networks with Node-wise Architecture

    Zhen Wang, Zhewei Wei, Yaliang Li, Weirui Kuang, Bolin Ding

  48. Disentangled Dynamic Heterogeneous Graph Learning for Opioid Overdose Prediction

    Qianlong Wen, Zhongyu Ouyang, Jianfei Zhang, Yiyue Qian, Yanfang Ye, Chuxu Zhang

  49. Robust Tensor Graph Convolutional Networks via T-SVD based Graph Augmentation

    Zhebin Wu, Lin Shu, Ziyue Xu, Yaomin Chang, Chuan Chen, Zibin Zheng

  50. Self-Supervised Hypergraph Transformer for Recommender Systems

    Lianghao Xia, Chao Huang, Chuxu Zhang

  51. Ultrahyperbolic Knowledge Graph Embeddings

    Bo Xiong, Shichao Zhu, Mojtaba Nayyeri, Chengjin Xu, Shirui Pan, Chuan Zhou, Steffen Staab

  52. Towards a Native Quantum Paradigm for Graph Representation Learning: A Sampling-based Recurrent Embedding Approach

    Ge Yan, Yehui Tang, Junchi Yan

  53. Enhancing Machine Learning Approaches for Graph Optimization Problems with Diversifying Graph Augmentation

    Chen-Hsu Yang, Chih-Ya Shen

  54. Multi-Behavior Hypergraph-Enhanced Transformer for Sequential Recommendation

    Yuhao Yang, Chao Huang, Lianghao Xia, Yuxuan Liang, Yanwei Yu, Chenliang Li

  55. TrajGAT: A Graph-based Long-term Dependency Modeling Approach for Trajectory Similarity Computation

    Di Yao, Haonan Hu, Lun Du, Gao Cong, Shi Han, Jingping Bi

  56. Learning the Evolutionary and Multi-scale Graph Structure for Multivariate Time Series Forecasting

    Junchen Ye, Zihan Liu, Bowen Du, Leilei Sun, Weimiao Li, Yanjie Fu, Hui Xiong

  57. Accurate Node Feature Estimation with Structured Variational Graph Autoencoder

    Jaemin Yoo, Hyunsik Jeon, Jinhong Jung, U Kang

  58. ROLAND: Graph Learning Framework for Dynamic Graphs

    Jiaxuan You, Tianyu Du, Jure Leskovec

  59. Multiplex Heterogeneous Graph Convolutional Network

    Pengyang Yu, Chaofan Fu, Yanwei Yu, Chao Huang, Zhongying Zhao, Junyu Dong

  60. Dual Bidirectional Graph Convolutional Networks for Zero-shot Node Classification

    Qin Yue, Jiye Liang, Junbiao Cui, Liang Bai

  61. Variational Graph Author Topic Modeling

    Delvin Ce Zhang, Hady Wirawan Lauw

  62. Few-shot Heterogeneous Graph Learning via Cross-domain Knowledge Transfer

    Qiannan Zhang, Xiaodong Wu, Qiang Yang, Chuxu Zhang, Xiangliang Zhang

  63. Model Degradation Hinders Deep Graph Neural Networks

    Wentao Zhang, Zeang Sheng, Ziqi Yin, Yuezihan Jiang, Yikuan Xia, Jun Gao, Zhi Yang, Bin Cui

  64. Improving Social Network Embedding via New Second-Order Continuous Graph Neural Networks

    Yanfu Zhang, Shangqian Gao, Jian Pei, Heng Huang

  65. COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning

    Yifei Zhang, Hao Zhu, Zixing Song, Piotr Koniusz, Irwin King

  66. Instant Graph Neural Networks for Dynamic Graphs

    Yanping Zheng, Hanzhi Wang, Zhewei Wei, Jiajun Liu, Sibo Wang

  67. How does Heterophily Impact the Robustness of Graph Neural Networks?: Theoretical Connections and Practical Implications

    Jiong Zhu, Junchen Jin, Donald Loveland, Michael T. Schaub, Danai Koutra

  68. Generalizable Floorplanner through Corner Block List Representation and Hypergraph Embedding

    Mohammad Amini, Zhanguang Zhang, Surya Penmetsa, Yingxue Zhang, Jianye Hao, Wulong Liu

  69. Company-as-Tribe: Company Financial Risk Assessment on Tribe-Style Graph with Hierarchical Graph Neural Networks

    Wendong Bi, Bingbing Xu, Xiaoqian Sun, Zidong Wang, Huawei Shen, Xueqi Cheng

  70. BrainNet: Epileptic Wave Detection from SEEG with Hierarchical Graph Diffusion Learning

    Junru Chen, Yang Yang, Tao Yu, Yingying Fan, Xiaolong Mo, Carl Yang

  71. Physics-Guided Graph Meta Learning for Predicting Water Temperature and Streamflow in Stream Networks

    Shengyu Chen, Jacob A. Zwart, Xiaowei Jia

  72. AntiBenford Subgraphs: Unsupervised Anomaly Detection in Financial Networks

    Tianyi Chen, Charalampos E. Tsourakakis

  73. Talent Demand-Supply Joint Prediction with Dynamic Heterogeneous Graph Enhanced Meta-Learning

    Zhuoning Guo, Hao Liu, Le Zhang, Qi Zhang, Hengshu Zhu, Hui Xiong

  74. Talent Demand-Supply Joint Prediction with Dynamic Heterogeneous Graph Enhanced Meta-Learning

    Zhuoning Guo, Hao Liu, Le Zhang, Qi Zhang, Hengshu Zhu, Hui Xiong

  75. Learning Sparse Latent Graph Representations for Anomaly Detection in Multivariate Time Series

    Siho Han, Simon S. Woo

  76. ERNIE-GeoL: A Geography-and-Language Pre-trained Model and its Applications in Baidu Maps

    Jizhou Huang, Haifeng Wang, Yibo Sun, Yunsheng Shi, Zhengjie Huang, An Zhuo, Shikun Feng

  77. Graph Neural Network Training and Data Tiering

    Seungwon Min, Kun Wu, Mert Hidayetoglu, Jinjun Xiong, Xiang Song, Wen-Mei Hwu

  78. GraphWorld: Fake Graphs Bring Real Insights for GNNs

    John Palowitch, Anton Tsitsulin, Brandon Mayer, Bryan Perozzi

  79. Improving Relevance Modeling via Heterogeneous Behavior Graph Learning in Bing Ads

    Bochen Pang, Chaozhuo Li, Yuming Liu, Jianxun Lian, Jianan Zhao, Hao Sun, Weiwei Deng, Xing Xie, Qi Zhang

  80. Friend Recommendations with Self-Rescaling Graph Neural Networks

    Xiran Song, Jianxun Lian, Hong Huang, Mingqi Wu, Hai Jin, Xing Xie

  81. A Graph Learning Based Framework for Billion-Scale Offline User Identification

    Daixin Wang, Zujian Weng, Zhengwei Wu, Zhiqiang Zhang, Peng Cui, Hongwei Zhao, Jun Zhou

  82. FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Package for Federated Graph Learning

    Zhen Wang, Weirui Kuang, Yuexiang Xie, Liuyi Yao, Yaliang Li, Bolin Ding, Jingren Zhou

  83. Connecting the Hosts: Street-Level IP Geolocation with Graph Neural Networks

    Zhiyuan Wang, Fan Zhou, Wenxuan Zeng, Goce Trajcevski, Chunjing Xiao, Yong Wang, Kai Chen

  84. Graph2Route: A Dynamic Spatial-Temporal Graph Neural Network for Pick-up and Delivery Route Prediction

    Haomin Wen, Youfang Lin, Xiaowei Mao, Fan Wu, Yiji Zhao, Haochen Wang, Jianbin Zheng, Lixia Wu, Haoyuan Hu, Huaiyu Wan

  85. Graph Neural Networks for Multimodal Single-Cell Data Integration

    Hongzhi Wen, Jiayuan Ding, Wei Jin, Yiqi Wang, Yuying Xie, Jiliang Tang

  86. Learning Large-scale Subsurface Simulations with a Hybrid Graph Network Simulator

    Tailin Wu, Qinchen Wang, Yinan Zhang, Rex Ying, Kaidi Cao, Rok Sosic, Ridwan Jalali, Hassan Hamam, Marko Maucec, Jure Leskovec

  87. Embedding Compression with Hashing for Efficient Representation Learning in Large-Scale Graph

    Chin-Chia Michael Yeh, Mengting Gu, Yan Zheng, Huiyuan Chen, Javid Ebrahimi, Zhongfang Zhuang, Junpeng Wang, Liang Wang, Wei Zhang

  88. Graph Attention Multi-Layer Perceptron

    Wentao Zhang, Ziqi Yin, Zeang Sheng, Yang Li, Wen Ouyang, Xiaosen Li, Yangyu Tao, Zhi Yang, Bin Cui

  89. Distributed Hybrid CPU and GPU training for Graph Neural Networks on Billion-Scale Heterogeneous Graphs

    Da Zheng, Xiang Song, Chengru Yang, Dominique LaSalle, George Karypis

  90. Dynamic Graph Segmentation for Deep Graph Neural Networks

    Johan Kok Zhi Kang, Suwei Yang, Suriya Venkatesan, Sien Yi Tan, Feng Cheng, Bingsheng He

  91. Uncertainty Quantification of Sparse Travel Demand Prediction with Spatial-Temporal Graph Neural Networks

    Dingyi Zhuang, Shenhao Wang, Haris N. Koutsopoulos, Jinhua Zhao

  1. Investigating Accuracy-Novelty Performance for Graph-based Collaborative Filtering

    Minghao Zhao, Le Wu, Yile Liang, Lei Chen, Jian Zhang, Qilin Deng, Kai Wang, Xudong Shen, Tangjie Lv, Runze Wu

  2. Hypergraph Contrastive Collaborative Filtering

    Lianghao Xia, Chao Huang, Yong Xu, Jiashu Zhao, Dawei Yin, Jimmy X. Huang

  3. Graph Trend Filtering Networks for Recommendation

    Wenqi Fan, Xiaorui Liu, Wei Jin, Xiangyu Zhao, Jiliang Tang, Qing Li

  4. Learning to Denoise Unreliable Interactions for Graph Collaborative Filtering

    Changxin Tian, Yuexiang Xie, Yaliang Li, Nan Yang, Wayne Xin Zhao

  5. Neighbour Interaction based Click-Through Rate Prediction via Graph-masked Transformer

    Erxue Min, Yu Rong, Tingyang Xu, Yatao Bian, Da Luo, Kangyi Lin, Junzhou Huang, Sophia Ananiadou, Peilin Zhao

  6. DAWAR: Diversity-aware Web APIs Recommendation for Mashup Creation based on Correlation Graph

    Wenwen Gong, Xuyun Zhang, Yifei Chen, Qiang He, Amin Beheshti, Xiaolong Xu, Chao Yan, Lianyong Qi

  7. Introducing Problem Schema with Hierarchical Exercise Graph for Knowledge Tracing

    Hanshuang Tong, Zhen Wang, Yun Zhou, Shiwei Tong, Wenyuan Han, Qi Liu

  8. Few-shot Node Classification on Attributed Networks with Graph Meta-learning

    Yonghao Liu, Mengyu Li, Ximing Li, Fausto Giunchiglia, Xiaoyue Feng, Renchu Guan

  9. Personalized Fashion Compatibility Modeling via Metapath-guided Heterogeneous Graph Learning

    Weili Guan, Fangkai Jiao, Xuemeng Song, Haokun Wen, Chung-Hsing Yeh, Xiaojun Chang

  10. KETCH: Knowledge Graph Enhanced Thread Recommendation in Healthcare Forums

    Limeng Cui, Dongwon Lee

  11. Post Processing Recommender Systems with Knowledge Graphs for Recency, Popularity, and Diversity of Explanations

    Giacomo Balloccu, Ludovico Boratto, Gianni Fenu, Mirko Marras

  12. Co-clustering Interactions via Attentive Hypergraph Neural Network

    Tianchi Yang, Cheng Yang, Luhao Zhang, Chuan Shi, Maodi Hu, Huaijun Liu, Tao Li, Dong Wang

  13. Incorporating Context Graph with Logical Reasoning for Inductive Relation Prediction

    Qika Lin, Jun Liu, Fangzhi Xu, Yudai Pan, Yifan Zhu, Lingling Zhang, Tianzhe Zhao

  14. Hybrid Transformer with Multi-level Fusion for Multimodal Knowledge Graph Completion

    Xiang Chen, Ningyu Zhang, Lei Li, Shumin Deng, Chuanqi Tan, Changliang Xu, Fei Huang, Luo Si, Huajun Chen

  15. Re-thinking Knowledge Graph Completion Evaluation from an Information Retrieval Perspective

    Ying Zhou, Xuanang Chen, Ben He, Zheng Ye, Le Sun

  16. Meta-Knowledge Transfer for Inductive Knowledge Graph Embedding

    Mingyang Chen, Wen Zhang, Yushan Zhu, Hongting Zhou, Zonggang Yuan, Changliang Xu, Huajun Chen

  17. Logiformer: A Two-Branch Graph Transformer Network for Interpretable Logical Reasoning

    Fangzhi Xu, Jun Liu, Qika Lin, Yudai Pan, Lingling Zhang

  18. Hierarchical Multi-Task Graph Recurrent Network for Next POI Recommendation

    Nicholas Lim, Bryan Hooi, See-Kiong Ng, Yong Liang Goh, Renrong Weng, Rui Tan

  19. Learning Graph-based Disentangled Representations for Next POI Recommendation

    Zhaobo Wang, Yanmin Zhu, Haobing Liu, Chunyang Wang

  20. Less is More: Reweighting Important Spectral Graph Features for Recommendation

    Shaowen Peng, Kazunari Sugiyama, Tsunenori Mine

  21. A Review-aware Graph Contrastive Learning Framework for Recommendation

    Jie Shuai, Kun Zhang, Le Wu, Peijie Sun, Richang Hong, Meng Wang, Yong Li

  22. Are Graph Augmentations Necessary?: Simple Graph Contrastive Learning for Recommendation

    Junliang Yu, Hongzhi Yin, Xin Xia, Tong Chen, Lizhen Cui, Quoc Viet Hung Nguyen

  23. Knowledge Graph Contrastive Learning for Recommendation

    Yuhao Yang, Chao Huang, Lianghao Xia, Chenliang Li

  24. Graph Adaptive Semantic Transfer for Cross-domain Sentiment Classification

    Kai Zhang, Qi Liu, Zhenya Huang, Mingyue Cheng, Kun Zhang, Mengdi Zhang, Wei Wu, Enhong Chen

  25. An Attribute-Driven Mirror Graph Network for Session-based Recommendation

    Siqi Lai, Erli Meng, Fan Zhang, Chenliang Li, Bin Wang, Aixin Sun

  26. AutoGSR: Neural Architecture Search for Graph-based Session Recommendation

    Jingfan Chen, Guanghui Zhu, Haojun Hou, Chunfeng Yuan, Yihua Huang

  27. Unsupervised Belief Representation Learning with Information-Theoretic Variational Graph Auto-Encoders

    Jinning Li, Huajie Shao, Dachun Sun, Ruijie Wang, Yuchen Yan, Jinyang Li, Shengzhong Liu, Hanghang Tong, Tarek F. Abdelzaher

  28. Multi-modal Graph Contrastive Learning for Micro-video Recommendation

    Zixuan Yi, Xi Wang, Iadh Ounis, Craig MacDonald

  29. Adversarial Graph Perturbations for Recommendations at Scale

    Huiyuan Chen, Kaixiong Zhou, Kwei-Herng Lai, Xia Hu, Fei Wang, Hao Yang

  30. Graph Capsule Network with a Dual Adaptive Mechanism

    Xiangping Zheng, Xun Liang, Bo Wu, Yuhui Guo, Xuan Zhang

  31. Enhancing Hypergraph Neural Networks with Intent Disentanglement for Session-based Recommendation

    Yinfeng Li, Chen Gao, Hengliang Luo, Depeng Jin, Yong Li

  32. Distilling Knowledge on Text Graph for Social Media Attribute Inference

    Quan Li, Xiaoting Li, Lingwei Chen, Dinghao Wu

  33. DH-HGCN: Dual Homogeneity Hypergraph Convolutional Network for Multiple Social Recommendations

    Jiadi Han, Qian Tao, Yufei Tang, Yuhan Xia

  34. GraFN: Semi-Supervised Node Classification on Graph with Few Labels via Non-Parametric Distribution Assignment

    Junseok Lee, Yunhak Oh, Yeonjun In, Namkyeong Lee, Dongmin Hyun, Chanyoung Park

  35. GraphAD: A Graph Neural Network for Entity-Wise Multivariate Time-Series Anomaly Detection

    Xu Chen, Qiu Qiu, Changshan Li, Kunqing Xie

  36. DisenCTR: Dynamic Graph-based Disentangled Representation for Click-Through Rate Prediction

    Yifan Wang, Yifang Qin, Fang Sun, Bo Zhang, Xuyang Hou, Ke Hu, Jia Cheng, Jun Lei, Ming Zhang

  37. An MLP-based Algorithm for Efficient Contrastive Graph Recommendations

    Siwei Liu, Iadh Ounis, Craig Macdonald

  38. Assessing Scientific Research Papers with Knowledge Graphs

    Kexuan Sun, Zhiqiang Qiu, Abel Salinas, Yuzhong Huang, Dong-Ho Lee, Daniel Benjamin, Fred Morstatter, Xiang Ren, Kristina Lerman, Jay Pujara

  39. MuchSUM: Multi-channel Graph Neural Network for Extractive Summarization

    Qianren Mao, Hongdong Zhu, Junnan Liu, Cheng Ji, Hao Peng, Jianxin Li, Lihong Wang, Zheng Wang

  40. LightSGCN: Powering Signed Graph Convolution Network for Link Sign Prediction with Simplified Architecture Design

    Haoxin Liu

  41. Space4HGNN: A Novel, Modularized and Reproducible Platform to Evaluate Heterogeneous Graph Neural Network

    Tianyu Zhao, Cheng Yang, Yibo Li, Quan Gan, Zhenyi Wang, Fengqi Liang, Huan Zhao, Yingxia Shao, Xiao Wang, Chuan Shi

  1. Sketch-GNN: Scalable Graph Neural Networks with Sublinear Training Complexity.

    Mucong Ding, Tahseen Rabbani, Bang An, Evan Wang, Furong Huang

  2. Beyond Real-world Benchmark Datasets: An Empirical Study of Node Classification with GNNs.

    Seiji Maekawa, Koki Noda, Yuya Sasaki, Makoto Onizuka

  3. Vision GNN: An Image is Worth Graph of Nodes.

    Kai Han, Yunhe Wang, Jianyuan Guo, Yehui Tang, Enhua Wu

  4. Does GNN Pretraining Help Molecular Representation?

    Ruoxi Sun, Hanjun Dai, Adams Wei Yu

  5. ReFactor GNNs: Revisiting Factorisation-based Models from a Message-Passing Perspective.

    Yihong Chen, Pushkar Mishra, Luca Franceschi, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel

  6. Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs.

    Cristian Bodnar, Francesco Di Giovanni, Benjamin Paul Chamberlain, Pietro Lió, Michael M. Bronstein

  7. OOD Link Prediction Generalization Capabilities of Message-Passing GNNs in Larger Test Graphs.

    Yangze Zhou, Gitta Kutyniok, Bruno Ribeiro

  8. MGNNI: Multiscale Graph Neural Networks with Implicit Layers.

    Juncheng Liu, Bryan Hooi, Kenji Kawaguchi, Xiaokui Xiao

  9. NeuroSchedule: A Novel Effective GNN-based Scheduling Method for High-level Synthesis.

    Jun Zeng, Mingyang Kou, Hailong Yao

  10. Learning-based Motion Planning in Dynamic Environments Using GNNs and Temporal Encoding.

    Ruipeng Zhang, Chenning Yu, Jingkai Chen, Chuchu Fan, Sicun Gao

  11. Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries.

    Fabrizio Frasca, Beatrice Bevilacqua, Michael M. Bronstein, Haggai Maron

  12. A Practical, Progressively-Expressive GNN.

    Lingxiao Zhao, Neil Shah, Leman Akoglu

  13. PhysGNN: A Physics-Driven Graph Neural Network Based Model for Predicting Soft Tissue Deformation in Image-Guided Neurosurgery.

    Yasmin Salehi, Dennis Giannacopoulos

  14. NAS-Bench-Graph: Benchmarking Graph Neural Architecture Search.

    Yijian Qin, Ziwei Zhang, Xin Wang, Zeyang Zhang, Wenwu Zhu

  15. Decoupled Self-supervised Learning for Graphs.

    Teng Xiao, Zhengyu Chen, Zhimeng Guo, Zeyang Zhuang, Suhang Wang

  16. ComENet: Towards Complete and Efficient Message Passing for 3D Molecular Graphs.

    Limei Wang, Yi Liu, Yuchao Lin, Haoran Liu, Shuiwang Ji

  17. Revisiting Heterophily For Graph Neural Networks.

    Sitao Luan, Chenqing Hua, Qincheng Lu, Jiaqi Zhu, Mingde Zhao, Shuyuan Zhang, Xiao-Wen Chang, Doina Precup

  18. Certifying Robust Graph Classification under Orthogonal Gromov-Wasserstein Threats.

    Hongwei Jin, Zishun Yu, Xinhua Zhang

  19. Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative.

    Tianxin Wei, Yuning You, Tianlong Chen, Yang Shen, Jingrui He, Zhangyang Wang

  20. GOOD: A Graph Out-of-Distribution Benchmark.

    Shurui Gui, Xiner Li, Limei Wang, Shuiwang Ji

  21. Not too little, not too much: a theoretical analysis of graph (over)smoothing.

    Nicolas Keriven

  22. Tree Mover's Distance: Bridging Graph Metrics and Stability of Graph Neural Networks.

    Ching-Yao Chuang, Stefanie Jegelka

  23. Revisiting Graph Contrastive Learning from the Perspective of Graph Spectrum.

    Nian Liu, Xiao Wang, Deyu Bo, Chuan Shi, Jian Pei

  24. S3GC: Scalable Self-Supervised Graph Clustering.

    Fnu Devvrit, Aditya Sinha, Inderjit S. Dhillon, Prateek Jain

  25. Pseudo-Riemannian Graph Convolutional Networks.

    Bo Xiong, Shichao Zhu, Nico Potyka, Shirui Pan, Chuan Zhou, Steffen Staab

  26. Unravelling the Performance of Physics-informed Graph Neural Networks for Dynamical Systems.

    Abishek Thangamuthu, Gunjan Kumar, Suresh Bishnoi, Ravinder Bhattoo, N. M. Anoop Krishnan, Sayan Ranu

  27. Graph Convolution Network based Recommender Systems: Learning Guarantee and Item Mixture Powered Strategy.

    Leyan Deng, Defu Lian, Chenwang Wu, Enhong Chen

  28. Redundancy-Free Message Passing for Graph Neural Networks.

    Rongqin Chen, Shenghui Zhang, Leong Hou U, Ye Li

  29. Association Graph Learning for Multi-Task Classification with Category Shifts.

    Jiayi Shen, Zehao Xiao, Xiantong Zhen, Cees Snoek, Marcel Worring

  30. EvenNet: Ignoring Odd-Hop Neighbors Improves Robustness of Graph Neural Networks.

    Runlin Lei, Zhen Wang, Yaliang Li, Bolin Ding, Zhewei Wei

  31. How Powerful are K-hop Message Passing Graph Neural Networks.

    Jiarui Feng, Yixin Chen, Fuhai Li, Anindya Sarkar, Muhan Zhang

  32. Generalization Analysis of Message Passing Neural Networks on Large Random Graphs.

    Sohir Maskey, Ron Levie, Yunseok Lee, Gitta Kutyniok

  33. Transition to Linearity of General Neural Networks with Directed Acyclic Graph Architecture.

    Libin Zhu, Chaoyue Liu, Misha Belkin

  34. A Comprehensive Study on Large-Scale Graph Training: Benchmarking and Rethinking.

    Keyu Duan, Zirui Liu, Peihao Wang, Wenqing Zheng, Kaixiong Zhou, Tianlong Chen, Xia Hu, Zhangyang Wang

  35. Geodesic Graph Neural Network for Efficient Graph Representation Learning.

    Lecheng Kong, Yixin Chen, Muhan Zhang

  36. High-Order Pooling for Graph Neural Networks with Tensor Decomposition.

    Chenqing Hua, Guillaume Rabusseau, Jian Tang

  37. Dynamic Graph Neural Networks Under Spatio-Temporal Distribution Shift.

    Zeyang Zhang, Xin Wang, Ziwei Zhang, Haoyang Li, Zhou Qin, Wenwu Zhu

  38. GraphQNTK: Quantum Neural Tangent Kernel for Graph Data.

    Yehui Tang, Junchi Yan

  39. On the Robustness of Graph Neural Diffusion to Topology Perturbations.

    Yang Song, Qiyu Kang, Sijie Wang, Kai Zhao, Wee Peng Tay

  40. Few-shot Relational Reasoning via Connection Subgraph Pretraining.

    Qian Huang, Hongyu Ren, Jure Leskovec

  41. Convolutional Neural Networks on Graphs with Chebyshev Approximation, Revisited.

    Mingguo He, Zhewei Wei, Ji-Rong Wen

  42. Evaluating Graph Generative Models with Contrastively Learned Features.

    Hamed Shirzad, Kaveh Hassani, Danica J. Sutherland

  43. An efficient graph generative model for navigating ultra-large combinatorial synthesis libraries.

    Aryan Pedawi, Pawel Gniewek, Chaoyi Chang, Brandon M. Anderson, Henry van den Bedem

  44. Are Defenses for Graph Neural Networks Robust?

    Felix Mujkanovic, Simon Geisler, Stephan Günnemann, Aleksandar Bojchevski

  45. Equivariant Graph Hierarchy-Based Neural Networks.

    Jiaqi Han, Wenbing Huang, Tingyang Xu, Yu Rong

  46. Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discrimination.

    Yizhen Zheng, Shirui Pan, Vincent C. S. Lee, Yu Zheng, Philip S. Yu

  47. Template based Graph Neural Network with Optimal Transport Distances.

    Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli, Titouan Vayer, Nicolas Courty

  48. Knowledge Distillation Improves Graph Structure Augmentation for Graph Neural Networks.

    Lirong Wu, Haitao Lin, Yufei Huang, Stan Z. Li

  49. Learning Invariant Graph Representations for Out-of-Distribution Generalization.

    Haoyang Li, Ziwei Zhang, Xin Wang, Wenwu Zhu

  50. Task-Agnostic Graph Explanations.

    Yaochen Xie, Sumeet Katariya, Xianfeng Tang, Edward W. Huang, Nikhil Rao, Karthik Subbian, Shuiwang Ji

  51. A Variational Edge Partition Model for Supervised Graph Representation Learning.

    Yilin He, Chaojie Wang, Hao Zhang, Bo Chen, Mingyuan Zhou

  52. CGLB: Benchmark Tasks for Continual Graph Learning.

    Xikun Zhang, Dongjin Song, Dacheng Tao

  53. What Makes Graph Neural Networks Miscalibrated?

    Hans Hao-Hsun Hsu, Yuesong Shen, Christian Tomani, Daniel Cremers

  54. Analyzing Data-Centric Properties for Graph Contrastive Learning.

    Puja Trivedi, Ekdeep Singh Lubana, Mark Heimann, Danai Koutra, Jayaraman J. Thiagarajan

  55. Learning Bipartite Graphs: Heavy Tails and Multiple Components.

    José Vinícius de Miranda Cardoso, Jiaxi Ying, Daniel P. Palomar

  56. Graph Self-supervised Learning with Accurate Discrepancy Learning.

    Dongki Kim, Jinheon Baek, Sung Ju Hwang

  57. Recipe for a General, Powerful, Scalable Graph Transformer.

    Ladislav Rampásek, Michael Galkin, Vijay Prakash Dwivedi, Anh Tuan Luu, Guy Wolf, Dominique Beaini

  58. Pure Transformers are Powerful Graph Learners.

    Jinwoo Kim, Dat Nguyen, Seonwoo Min, Sungjun Cho, Moontae Lee, Honglak Lee, Seunghoon Hong

  59. Periodic Graph Transformers for Crystal Material Property Prediction.

    Keqiang Yan, Yi Liu, Yuchao Lin, Shuiwang Ji

  60. Co-Modality Graph Contrastive Learning for Imbalanced Node Classification.

    Yiyue Qian, Chunhui Zhang, Yiming Zhang, Qianlong Wen, Yanfang Ye, Chuxu Zhang

  61. Learning NP-Hard Multi-Agent Assignment Planning using GNN: Inference on a Random Graph and Provable Auction-Fitted Q-learning.

    Hyunwook Kang, Taehwan Kwon, Jinkyoo Park, James R. Morrison

  62. Learning to Sample and Aggregate: Few-shot Reasoning over Temporal Knowledge Graphs.

    Ruijie Wang, Zheng Li, Dachun Sun, Shengzhong Liu, Jinning Li, Bing Yin, Tarek F. Abdelzaher

  63. Self-supervised Heterogeneous Graph Pre-training Based on Structural Clustering.

    Yaming Yang, Ziyu Guan, Zhe Wang, Wei Zhao, Cai Xu, Weigang Lu, Jianbin Huang

  64. Neural Topological Ordering for Computation Graphs.

    Mukul Gagrani, Corrado Rainone, Yang Yang, Harris Teague, Wonseok Jeon, Roberto Bondesan, Herke van Hoof, Christopher Lott, Weiliang Will Zeng, Piero Zappi

  65. Graph Learning Assisted Multi-Objective Integer Programming.

    Yaoxin Wu, Wen Song, Zhiguang Cao, Jie Zhang, Abhishek Gupta, Mingyan Lin

  66. Exact Shape Correspondence via 2D graph convolution.

    Barakeel Fanseu Kamhoua, Lin Zhang, Yongqiang Chen, Han Yang, Kaili Ma, Bo Han, Bo Li, James Cheng

  67. SHINE: SubHypergraph Inductive Neural nEtwork.

    Yuan Luo

  68. Multivariate Time-Series Forecasting with Temporal Polynomial Graph Neural Networks.

    Yijing Liu, Qinxian Liu, Jian-Wei Zhang, Haozhe Feng, Zhongwei Wang, Zihan Zhou, Wei Chen

  69. Graph Neural Networks with Adaptive Readouts.

    David Buterez, Jon Paul Janet, Steven J. Kiddle, Dino Oglic, Pietro Liò

  70. GStarX: Explaining Graph Neural Networks with Structure-Aware Cooperative Games.

    Shichang Zhang, Yozen Liu, Neil Shah, Yizhou Sun

  71. Neural Temporal Walks: Motif-Aware Representation Learning on Continuous-Time Dynamic Graphs.

    Ming Jin, Yuan-Fang Li, Shirui Pan

  72. OOD Link Prediction Generalization Capabilities of Message-Passing GNNs in Larger Test Graphs.

    Yangze Zhou, Gitta Kutyniok, Bruno Ribeiro

  73. Versatile Multi-stage Graph Neural Network for Circuit Representation.

    Shuwen Yang, Zhihao Yang, Dong Li, Yingxue Zhang, Zhanguang Zhang, Guojie Song, Jianye Hao

  74. Contrastive Graph Structure Learning via Information Bottleneck for Recommendation.

    Chunyu Wei, Jian Liang, Di Liu, Fei Wang

  75. Graph Neural Networks are Dynamic Programmers.

    Andrew Joseph Dudzik, Petar Velickovic

  76. Ordered Subgraph Aggregation Networks.

    Chendi Qian, Gaurav Rattan, Floris Geerts, Mathias Niepert, Christopher Morris

  77. Hierarchical Graph Transformer with Adaptive Node Sampling.

    Zaixi Zhang, Qi Liu, Qingyong Hu, Chee-Kong Lee

  78. MGNNI: Multiscale Graph Neural Networks with Implicit Layers.

    Juncheng Liu, Bryan Hooi, Kenji Kawaguchi, Xiaokui Xiao

  79. Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs.

    Yongqiang Chen, Yonggang Zhang, Yatao Bian, Han Yang, Kaili Ma, Binghui Xie, Tongliang Liu, Bo Han, James Cheng

  80. Long Range Graph Benchmark.

    Vijay Prakash Dwivedi, Ladislav Rampásek, Michael Galkin, Ali Parviz, Guy Wolf, Anh Tuan Luu, Dominique Beaini

  81. GREED: A Neural Framework for Learning Graph Distance Functions.

    Rishabh Ranjan, Siddharth Grover, Sourav Medya, Venkatesan T. Chakaravarthy, Yogish Sabharwal, Sayan Ranu

  82. Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRank.

    Alessandro Epasto, Vahab Mirrokni, Bryan Perozzi, Anton Tsitsulin, Peilin Zhong

  83. DGraph: A Large-Scale Financial Dataset for Graph Anomaly Detection.

    Xuanwen Huang, Yang Yang, Yang Wang, Chunping Wang, Zhisheng Zhang, Jiarong Xu, Lei Chen, Michalis Vazirgiannis

  84. Contrastive Language-Image Pre-Training with Knowledge Graphs.

    Xuran Pan, Tianzhu Ye, Dongchen Han, Shiji Song, Gao Huang

  85. Physics-Embedded Neural Networks: Graph Neural PDE Solvers with Mixed Boundary Conditions.

    Masanobu Horie, Naoto Mitsume

  86. Dual-discriminative Graph Neural Network for Imbalanced Graph-level Anomaly Detection.

    Ge Zhang, Zhenyu Yang, Jia Wu, Jian Yang, Shan Xue, Hao Peng, Jianlin Su, Chuan Zhou, Quan Z. Sheng, Leman Akoglu, Charu C. Aggarwal

  87. Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure.

    Shaohua Fan, Xiao Wang, Yanhu Mo, Chuan Shi, Jian Tang

  88. Non-Linear Coordination Graphs.

    Yipeng Kang, Tonghan Wang, Qianlan Yang, Xiaoran Wu, Chongjie Zhang

  89. CLEAR: Generative Counterfactual Explanations on Graphs.

    Jing Ma, Ruocheng Guo, Saumitra Mishra, Aidong Zhang, Jundong Li

  90. Learning Physical Dynamics with Subequivariant Graph Neural Networks.

    Jiaqi Han, Wenbing Huang, Hengbo Ma, Jiachen Li, Josh Tenenbaum, Chuang Gan

  91. BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs.

    Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, Lichao Sun, Jundong Li, George H. Chen, Zhihao Jia, Philip S. Yu

  92. Graphein - a Python Library for Geometric Deep Learning and Network Analysis on Biomolecular Structures and Interaction Networks.

    Arian R. Jamasb, Ramón Viñas Torné, Eric Ma, Yuanqi Du, Charles Harris, Kexin Huang, Dominic Hall, Pietro Lió, Tom L. Blundell

  93. Simplified Graph Convolution with Heterophily.

    Sudhanshu Chanpuriya, Cameron Musco

  94. Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks.

    Anders Aamand, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Ronitt Rubinfeld, Nicholas Schiefer, Sandeep Silwal, Tal Wagner

  95. Zero-shot Transfer Learning within a Heterogeneous Graph via Knowledge Transfer Networks.

    Minji Yoon, John Palowitch, Dustin Zelle, Ziniu Hu, Ruslan Salakhutdinov, Bryan Perozzi

  96. NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classification.

    Qitian Wu, Wentao Zhao, Zenan Li, David P. Wipf, Junchi Yan

  97. Parameter-free Dynamic Graph Embedding for Link Prediction.

    Jiahao Liu, Dongsheng Li, Hansu Gu, Tun Lu, Peng Zhang, Ning Gu

  98. Towards Reasonable Budget Allocation in Untargeted Graph Structure Attacks via Gradient Debias.

    Zihan Liu, Yun Luo, Lirong Wu, Zicheng Liu, Stan Z. Li

  99. Label-invariant Augmentation for Semi-Supervised Graph Classification.

    Han Yue, Chunhui Zhang, Chuxu Zhang, Hongfu Liu

  100. Geometric Knowledge Distillation: Topology Compression for Graph Neural Networks.

    Chenxiao Yang, Qitian Wu, Junchi Yan

  101. Learning Articulated Rigid Body Dynamics with Lagrangian Graph Neural Network.

    Ravinder Bhattoo, Sayan Ranu, N. M. Anoop Krishnan

  102. GraphDE: A Generative Framework for Debiased Learning and Out-of-Distribution Detection on Graphs.

    Zenan Li, Qitian Wu, Fan Nie, Junchi Yan

  103. Micro and Macro Level Graph Modeling for Graph Variational Auto-Encoders.

    Kiarash Zahirnia, Oliver Schulte, Parmis Nadaf, Ke Li

  104. Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries.

    Fabrizio Frasca, Beatrice Bevilacqua, Michael M. Bronstein, Haggai Maron

  105. Symmetry-induced Disentanglement on Graphs.

    Giangiacomo Mercatali, André Freitas, Vikas Garg

  106. SizeShiftReg: a Regularization Method for Improving Size-Generalization in Graph Neural Networks.

    Davide Buffelli, Pietro Lió, Fabio Vandin

  107. Learning to Compare Nodes in Branch and Bound with Graph Neural Networks.

    Abdel Ghani Labassi, Didier Chételat, Andrea Lodi

  108. Learning to Reconstruct Missing Data from Spatiotemporal Graphs with Sparse Observations.

    Ivan Marisca, Andrea Cini, Cesare Alippi

  109. Robust Graph Structure Learning via Multiple Statistical Tests.

    Yaohua Wang, Fangyi Zhang, Ming Lin, Senzhang Wang, Xiuyu Sun, Rong Jin

  110. Maximum Common Subgraph Guided Graph Retrieval: Late and Early Interaction Networks.

    Indradyumna Roy, Soumen Chakrabarti, Abir De

  111. Provably expressive temporal graph networks.

    Amauri H. Souza, Diego Mesquita, Samuel Kaski, Vikas Garg

  112. Uncovering the Structural Fairness in Graph Contrastive Learning.

    Ruijia Wang, Xiao Wang, Chuan Shi, Le Song

  113. On the Discrimination Risk of Mean Aggregation Feature Imputation in Graphs.

    Arjun Subramonian, Kai-Wei Chang, Yizhou Sun

  114. Randomized Message-Interception Smoothing: Gray-box Certificates for Graph Neural Networks.

    Yan Scholten, Jan Schuchardt, Simon Geisler, Aleksandar Bojchevski, Stephan Günnemann

  115. Neural Approximation of Graph Topological Features.

    Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang, Yusu Wang, Chao Chen

  116. Understanding Non-linearity in Graph Neural Networks from the Bayesian-Inference Perspective.

    Rongzhe Wei, Haoteng Yin, Junteng Jia, Austin R. Benson, Pan Li

  117. Graph Neural Network Bandits.

    Parnian Kassraie, Andreas Krause, Ilija Bogunovic

  118. Chartalist: Labeled Graph Datasets for UTXO and Account-based Blockchains.

    Kiarash Shamsi, Friedhelm Victor, Murat Kantarcioglu, Yulia R. Gel, Cuneyt Gurcan Akcora

  119. TwiBot-22: Towards Graph-Based Twitter Bot Detection.

    Shangbin Feng, Zhaoxuan Tan, Herun Wan, Ningnan Wang, Zilong Chen, Binchi Zhang, Qinghua Zheng, Wenqian Zhang, Zhenyu Lei, Shujie Yang, Xinshun Feng, Qingyue Zhang, Hongrui Wang, Yuhan Liu, Yuyang Bai, Heng Wang, Zijian Cai, Yanbo Wang, Lijing Zheng, Zihan Ma, Jundong Li, Minnan Luo

  120. Deep Generative Model for Periodic Graphs.

    Shiyu Wang, Xiaojie Guo, Liang Zhao

  121. PhysGNN: A Physics-Driven Graph Neural Network Based Model for Predicting Soft Tissue Deformation in Image-Guided Neurosurgery.

    Yasmin Salehi, Dennis Giannacopoulos

  122. Deep Bidirectional Language-Knowledge Graph Pretraining.

    Michihiro Yasunaga, Antoine Bosselut, Hongyu Ren, Xikun Zhang, Christopher D. Manning, Percy Liang, Jure Leskovec

  123. CryptoGCN: Fast and Scalable Homomorphically Encrypted Graph Convolutional Network Inference.

    Ran Ran, Wei Wang, Quan Gang, Jieming Yin, Nuo Xu, Wujie Wen

  124. Descent Steps of a Relation-Aware Energy Produce Heterogeneous Graph Neural Networks

    Hongjoon Ahn, Yongyi Yang, Quan Gan, Taesup Moon, David P. Wipf

  125. Graph Reordering for Cache-Efficient Near Neighbor Search.

    Benjamin Coleman, Santiago Segarra, Alexander J. Smola, Anshumali Shrivastava

  126. Graph Few-shot Learning with Task-specific Structures.

    Song Wang, Chen Chen, Jundong Li

  127. OTKGE: Multi-modal Knowledge Graph Embeddings via Optimal Transport.

    Zongsheng Cao, Qianqian Xu, Zhiyong Yang, Yuan He, Xiaochun Cao, Qingming Huang

  1. KRAF: A Flexible Advertising Framework using Knowledge Graph-Enriched Multi-Agent Reinforcement Learning.

    Jose A. Ayala-Romero, Péter Mernyei, Bichen Shi, Diego Mazón

  2. Memory Graph with Message Rehearsal for Multi-Turn Dialogue Generation.

    Xiaoyu Cai, Yao Fu, Hong Zhao, Weihao Jiang, Shiliang Pu

  3. Towards Self-supervised Learning on Graphs with Heterophily.

    Jingfan Chen, Guanghui Zhu, Yifan Qi, Chunfeng Yuan, Yihua Huang

  4. GCF-RD: A Graph-based Contrastive Framework for Semi-Supervised Learning on Relational Databases.

    Runjin Chen, Tong Li, Yanyan Shen, Luyu Qiu, Kaidi Li, Caleb Chen Cao

  5. Explainable Link Prediction in Knowledge Hypergraphs.

    Zirui Chen, Xin Wang, Chenxu Wang, Jianxin Li

  6. Finding Heterophilic Neighbors via Confidence-based Subgraph Matching for Semi-supervised Node Classification.

    Yoonhyuk Choi, Jiho Choi, Taewook Ko, Hyungho Byun, Chong-Kwon Kim

  7. Inductive Knowledge Graph Reasoning for Multi-batch Emerging Entities.

    Yuanning Cui, Yuxin Wang, Zequn Sun, Wenqiang Liu, Yiqiao Jiang, Kexin Han, Wei Hu

  8. Higher-order Clustering and Pooling for Graph Neural Networks.

    Alexandre Duval, Fragkiskos D. Malliaros

  9. MGMAE: Molecular Representation Learning by Reconstructing Heterogeneous Graphs with A High Mask Ratio.

    Jinjia Feng, Zhen Wang, Yaliang Li, Bolin Ding, Zhewei Wei, Hongteng Xu

  10. GraTO: Graph Neural Network Framework Tackling Over-smoothing with Neural Architecture Search.

    Xinshun Feng, Herun Wan, Shangbin Feng, Hongrui Wang, Qinghua Zheng, Jun Zhou, Minnan Luo

  11. Modeling Dynamic Heterogeneous Graph and Node Importance for Future Citation Prediction.

    Hao Geng, Deqing Wang, Fuzhen Zhuang, Xuehua Ming, Chenguang Du, Ting Jiang, Haolong Guo, Rui Liu

  12. ITSM-GCN: Informative Training Sample Mining for Graph Convolutional Network-based Collaborative Filtering.

    Kaiqi Gong, Xiao Song, Senzhang Wang, Songsong Liu, Yong Li

  13. Evolutionary Preference Learning via Graph Nested GRU ODE for Session-based Recommendation.

    Jiayan Guo, Peiyan Zhang, Chaozhuo Li, Xing Xie, Yan Zhang, Sunghun Kim

  14. Multi-Aggregator Time-Warping Heterogeneous Graph Neural Network for Personalized Micro-Video Recommendation.

    Jinkun Han, Wei Li, Zhipeng Cai, Yingshu Li

  15. Cross-Domain Aspect Extraction using Transformers Augmented with Knowledge Graphs.

    Phillip Howard, Arden Ma, Vasudev Lal, Ana Paula Simões, Daniel Korat, Oren Pereg, Moshe Wasserblat, Gadi Singer

  16. Discovering Fine-Grained Semantics in Knowledge Graph Relations.

    Nitisha Jain, Ralf Krestel

  17. Extracting Drug-drug Interactions from Biomedical Texts using Knowledge Graph Embeddings and Multi-focal Loss.

    Xin Jin, Xia Sun, Jiacheng Chen, Richard F. E. Sutcliffe

  18. X-GOAL: Multiplex Heterogeneous Graph Prototypical Contrastive Learning.

    Baoyu Jing, Shengyu Feng, Yuejia Xiang, Xi Chen, Yu Chen, Hanghang Tong

  19. Contrastive Representation Learning for Conversational Question Answering over Knowledge Graphs.

    Endri Kacupaj, Kuldeep Singh, Maria Maleshkova, Jens Lehmann

  20. SWAG-Net: Semantic Word-Aware Graph Network for Temporal Video Grounding.

    Sunoh Kim, Taegil Ha, Kimin Yun, Jin Young Choi

  21. Relational Self-Supervised Learning on Graphs.

    Namkyeong Lee, Dongmin Hyun, Junseok Lee, Chanyoung Park

  22. Automated Spatio-Temporal Synchronous Modeling with Multiple Graphs for Traffic Prediction.

    Fuxian Li, Huan Yan, Guangyin Jin, Yue Liu, Yong Li, Depeng Jin

  23. MDGCF: Multi-Dependency Graph Collaborative Filtering with Neighborhood- and Homogeneous-level Dependencies.

    Guohui Li, Zhiqiang Guo, Jianjun Li, Chaoyang Wang

  24. Heterogeneous Graph Attention Network for Drug-Target Interaction Prediction.

    Mei Li, Xiangrui Cai, Linyu Li, Sihan Xu, Hua Ji

  25. Spatiotemporal-aware Session-based Recommendation with Graph Neural Networks.

    Yinfeng Li, Chen Gao, Xiaoyi Du, Huazhou Wei, Hengliang Luo, Depeng Jin, Yong Li

  26. Dynamic Network Embedding via Temporal Path Adjacency Matrix Factorization.

    Zhuoming Li, Darong Lai

  27. DA-Net: Distributed Attention Network for Temporal Knowledge Graph Reasoning.

    Kangzheng Liu, Feng Zhao, Hongxu Chen, Yicong Li, Guandong Xu, Hai Jin

  28. Unsupervised Hierarchical Graph Pooling via Substructure-Sensitive Mutual Information Maximization.

    Ning Liu, Songlei Jian, Dongsheng Li, Hongzuo Xu

  29. HeGA: Heterogeneous Graph Aggregation Network for Trajectory Prediction in High-Density Traffic.

    Shuncheng Liu, Xu Chen, Ziniu Wu, Liwei Deng, Han Su, Kai Zheng

  30. I Know What You Do Not Know: Knowledge Graph Embedding via Co-distillation Learning.

    Yang Liu, Zequn Sun, Guangyao Li, Wei Hu

  31. Social Graph Transformer Networks for Pedestrian Trajectory Prediction in Complex Social Scenarios.

    Yao Liu, Lina Yao, Binghao Li, Xianzhi Wang, Claude Sammut

  32. Are Gradients on Graph Structure Reliable in Gray-box Attacks?

    Zihan Liu, Yun Luo, Lirong Wu, Siyuan Li, Zicheng Liu, Stan Z. Li

  33. HySAGE: A Hybrid Static and Adaptive Graph Embedding Network for Context-Drifting Recommendations.

    Sichun Luo, Xinyi Zhang, Yuanzhang Xiao, Linqi Song

  34. DEMO: Disentangled Molecular Graph Generation via an Invertible Flow Model.

    Changsheng Ma, Qiang Yang, Xin Gao, Xiangliang Zhang

  35. Hierarchical Spatio-Temporal Graph Neural Networks for Pandemic Forecasting.

    Yihong Ma, Patrick Gérard, Yijun Tian, Zhichun Guo, Nitesh V. Chawla

  36. Adaptive Re-Ranking with a Corpus Graph.

    Sean MacAvaney, Nicola Tonellotto, Craig Macdonald

  37. Automatic Meta-Path Discovery for Effective Graph-Based Recommendation.

    Wentao Ning, Reynold Cheng, Jiajun Shen, Nur Al Hasan Haldar, Ben Kao, Xiao Yan, Nan Huo, Wai Kit Lam, Tian Li, Bo Tang

  38. SVD-GCN: A Simplified Graph Convolution Paradigm for Recommendation.

    Shaowen Peng, Kazunari Sugiyama, Tsunenori Mine

  39. Malicious Repositories Detection with Adversarial Heterogeneous Graph Contrastive Learning.

    Yiyue Qian, Yiming Zhang, Nitesh V. Chawla, Yanfang Ye, Chuxu Zhang

  40. Reinforced Continual Learning for Graphs.

    Appan Rakaraddi, Siew-Kei Lam, Mahardhika Pratama, Marcus de Carvalho

  41. From Known to Unknown: Quality-aware Self-improving Graph Neural Network For Open Set Social Event Detection.

    Jiaqian Ren, Lei Jiang, Hao Peng, Yuwei Cao, Jia Wu, Philip S. Yu, Lifang He

  42. Graph Based Long-Term And Short-Term Interest Model for Click-Through Rate Prediction.

    Huinan Sun, Guangliang Yu, Pengye Zhang, Bo Zhang, Xingxing Wang, Dong Wang

  43. A Self-supervised Riemannian GNN with Time Varying Curvature for Temporal Graph Learning.

    Li Sun, Junda Ye, Hao Peng, Philip S. Yu

  44. Position-aware Structure Learning for Graph Topology-imbalance by Relieving Under-reaching and Over-squashing.

    Qingyun Sun, Jianxin Li, Haonan Yuan, Xingcheng Fu, Hao Peng, Cheng Ji, Qian Li, Philip S. Yu

  45. Temporality- and Frequency-aware Graph Contrastive Learning for Temporal Network.

    Shiyin Tan, Jingyi You, Dongyuan Li

  46. Interpretable Emotion Analysis Based on Knowledge Graph and OCC Model.

    Shuo Wang, Yifei Zhang, Bochen Lin, Boxun Li

  47. AdaGCL: Adaptive Subgraph Contrastive Learning to Generalize Large-scale Graph Training.

    Yili Wang, Kaixiong Zhou, Rui Miao, Ninghao Liu, Xin Wang

  48. Imbalanced Graph Classification via Graph-of-Graph Neural Networks.

    Yu Wang, Yuying Zhao, Neil Shah, Tyler Derr

  49. Dynamic Hypergraph Learning for Collaborative Filtering.

    Chunyu Wei, Jian Liang, Bing Bai, Di Liu

  50. Large-scale Entity Alignment via Knowledge Graph Merging, Partitioning and Embedding.

    Kexuan Xin, Zequn Sun, Wen Hua, Wei Hu, Jianfeng Qu, Xiaofang Zhou

  51. Taxonomy-Enhanced Graph Neural Networks.

    Lingjun Xu, Shiyin Zhang, Guojie Song, Junshan Wang, Tianshu Wu, Guojun Liu

  52. Semi-supervised Hypergraph Node Classification on Hypergraph Line Expansion.

    Chaoqi Yang, Ruijie Wang, Shuochao Yao, Tarek F. Abdelzaher

  53. GROWN+UP: A "Graph Representation Of a Webpage" Network Utilizing Pre-training.

    Benedict Yeoh, Huijuan Wang

  54. Scalable Graph Sampling on GPUs with Compressed Graph.

    Hongbo Yin, Yingxia Shao, Xupeng Miao, Yawen Li, Bin Cui

  55. The Interaction Graph Auto-encoder Network Based on Topology-aware for Transferable Recommendation.

    Ruiyun Yu, Kang Yang, Bingyang Guo

  56. Cognize Yourself: Graph Pre-Training via Core Graph Cognizing and Differentiating.

    Tao Yu, Yao Fu, Linghui Hu, Huizhao Wang, Weihao Jiang, Shiliang Pu

  57. LTE4G: Long-Tail Experts for Graph Neural Networks.

    Sukwon Yun, Kibum Kim, Kanghoon Yoon, Chanyoung Park

  58. Look Twice as Much as You Say: Scene Graph Contrastive Learning for Self-Supervised Image Caption Generation.

    Chunhui Zhang, Chao Huang, Youhuan Li, Xiangliang Zhang, Yanfang Ye, Chuxu Zhang

  59. Along the Time: Timeline-traced Embedding for Temporal Knowledge Graph Completion.

    Fuwei Zhang, Zhao Zhang, Xiang Ao, Fuzhen Zhuang, Yongjun Xu, Qing He

  60. Handling RDF Streams: Harmonizing Subgraph Matching, Adaptive Incremental Maintenance, and Matching-free Updates Together.

    Qianzhen Zhang, Deke Guo, Xiang Zhao, Lailong Luo

  61. Contrastive Knowledge Graph Error Detection.

    Qinggang Zhang, Junnan Dong, Keyu Duan, Xiao Huang, Yezi Liu, Linchuan Xu

  62. A Simple Meta-path-free Framework for Heterogeneous Network Embedding.

    Rui Zhang, Arthur Zimek, Peter Schneider-Kamp

  63. Two-Level Graph Path Reasoning for Conversational Recommendation with User Realistic Preference.

    Rongmei Zhao, Shenggen Ju, Jian Peng, Ning Yang, Fanli Yan, Siyu Sun

  64. MentorGNN: Deriving Curriculum for Pre-Training GNNs.

    Dawei Zhou, Lecheng Zheng, Dongqi Fu, Jiawei Han, Jingrui He

  65. D-HYPR: Harnessing Neighborhood Modeling and Asymmetry Preservation for Digraph Representation Learning.

    Honglu Zhou, Advith Chegu, Samuel S. Sohn, Zuohui Fu, Gerard de Melo, Mubbasir Kapadia

  66. Decoupled Hyperbolic Graph Attention Network for Modeling Substitutable and Complementary Item Relationships.

    Zhiheng Zhou, Tao Wang, Linfang Hou, Xinyuan Zhou, Mian Ma, Zhuoye Ding

  67. Robust Node Classification on Graphs: Jointly from Bayesian Label Transition and Topology-based Label Propagation.

    Jun Zhuang, Mohammad Al Hasan

  68. Tiger: Transferable Interest Graph Embedding for Domain-Level Zero-Shot Recommendation.

    Jianhuan Zhuo, Jianxun Lian, Lanling Xu, Ming Gong, Linjun Shou, Daxin Jiang, Xing Xie, Yinliang Yue

  69. Efficient and Effective SPARQL Autocompletion on Very Large Knowledge Graphs.

    Hannah Bast, Johannes Kalmbach, Theresa Klumpp, Florian Kramer, Niklas Schnelle

  70. Graph Neural Networks Pretraining Through Inherent Supervision for Molecular Property Prediction.

    Roy Benjamin, Uriel Singer, Kira Radinsky

  71. GIFT: Graph-guIded Feature Transfer for Cold-Start Video Click-Through Rate Prediction.

    Yi Cao, Sihao Hu, Yu Gong, Zhao Li, Yazheng Yang, Qingwen Liu, Shouling Ji

  72. DuETA: Traffic Congestion Propagation Pattern Modeling via Efficient Graph Learning for ETA Prediction at Baidu Maps.

    Jizhou Huang, Zhengjie Huang, Xiaomin Fang, Shikun Feng, Xuyi Chen, Jiaxiang Liu, Haitao Yuan, Haifeng Wang

  73. PlatoGL: Effective and Scalable Deep Graph Learning System for Graph-enhanced Real-Time Recommendation.

    Dandan Lin, Shijie Sun, Jingtao Ding, Xuehan Ke, Hao Gu, Xing Huang, Chonggang Song, Xuri Zhang, Lingling Yi, Jie Wen, Chuan Chen

  74. BRIGHT - Graph Neural Networks in Real-time Fraud Detection.

    Mingxuan Lu, Zhichao Han, Susie Xi Rao, Zitao Zhang, Yang Zhao, Yinan Shan, Ramesh Raghunathan, Ce Zhang, Jiawei Jiang

  75. Temporal and Heterogeneous Graph Neural Network for Financial Time Series Prediction.

    Sheng Xiang, Dawei Cheng, Chencheng Shang, Ying Zhang, Yuqi Liang

  76. Graph-based Weakly Supervised Framework for Semantic Relevance Learning in E-commerce.

    Zhiyuan Zeng, Yuzhi Huang, Tianshu Wu, Hongbo Deng, Jian Xu, Bo Zheng

  77. Cross-Domain Product Search with Knowledge Graph.

    Rui Zhu, Yiming Zhao, Wei Qu, Zhongyi Liu, Chenliang Li

  78. Interpretability of BERT Latent Space through Knowledge Graphs.

    Vito Walter Anelli, Giovanni Maria Biancofiore, Alessandro De Bellis, Tommaso Di Noia, Eugenio Di Sciascio

  79. CS-MLGCN: Multiplex Graph Convolutional Networks for Community Search in Multiplex Networks.

    Ali Behrouz, Farnoosh Hashemi

  80. Scalable Graph Representation Learning via Locality-Sensitive Hashing.

    Xiusi Chen, Jyun-Yu Jiang, Wei Wang

  81. On Positional and Structural Node Features for Graph Neural Networks on Non-attributed Graphs.

    Hejie Cui, Zijie Lu, Pan Li, Carl Yang

  82. Adaptive Graph Spatial-Temporal Transformer Network for Traffic Forecasting.

    Aosong Feng, Leandros Tassiulas

  83. Subspace Co-clustering with Two-Way Graph Convolution.

    Chakib Fettal, Lazhar Labiod, Mohamed Nadif

  84. OpenHGNN: An Open Source Toolkit for Heterogeneous Graph Neural Network.

    Hui Han, Tianyu Zhao, Cheng Yang, Hongyi Zhang, Yaoqi Liu, Xiao Wang, Chuan Shi

  85. AMinerGNN: Heterogeneous Graph Neural Network for Paper Click-through Rate Prediction with Fusion Query.

    Zepeng Huai, Zhe Wang, Yifan Zhu, Peng Zhang

  86. LGP: Few-Shot Class-Evolutionary Learning on Dynamic Graphs.

    Tiancheng Huang, Feng Zhao, Donglin Wang

  87. RealGraphGPU: A High-Performance GPU-Based Graph Engine toward Large-Scale Real-World Network Analysis.

    Myung-Hwan Jang, Yun-Yong Ko, Dongkyu Jeong, Jeong-Min Park, Sang-Wook Kim

  88. GReS: Graphical Cross-domain Recommendation for Supply Chain Platform.

    Zhiwen Jing, Ziliang Zhao, Yang Feng, Xiaochen Ma, Nan Wu, Shengqiao Kang, Cheng Yang, Yujia Zhang, Hao Guo

  89. Commonsense Knowledge Base Completion with Relational Graph Attention Network and Pre-trained Language Model.

    Jinhao Ju, Deqing Yang, Jingping Liu

  90. Models and Benchmarks for Representation Learning of Partially Observed Subgraphs.

    Dongkwan Kim, Jiho Jin, Jaimeen Ahn, Alice Oh

  91. Bootstrapped Knowledge Graph Embedding based on Neighbor Expansion.

    Jun Seon Kim, Seong-Jin Ahn, Myoung Ho Kim

  92. Debiasing Neighbor Aggregation for Graph Neural Network in Recommender Systems.

    Minseok Kim, Jinoh Oh, Jaeyoung Do, Sungjin Lee

  93. Dual-Augment Graph Neural Network for Fraud Detection.

    Qiutong Li, Yanshen He, Cong Xu, Feng Wu, Jianliang Gao, Zhao Li

  94. SmartQuery: An Active Learning Framework for Graph Neural Networks through Hybrid Uncertainty Reduction.

    Xiaoting Li, Yuhang Wu, Vineeth Rakesh, Yusan Lin, Hao Yang, Fei Wang

  95. Heterogeneous Hypergraph Neural Network for Friend Recommendation with Human Mobility.

    Yongkang Li, Zipei Fan, Jixiao Zhang, Dengheng Shi, Tianqi Xu, Du Yin, Jinliang Deng, Xuan Song

  96. Embedding Global and Local Influences for Dynamic Graphs.

    Meng Liu, Jiaming Wu, Yong Liu

  97. Memory Augmented Graph Learning Networks for Multivariate Time Series Forecasting.

    Xiangyue Liu, Xinqi Lyu, Xiangchi Zhang, Jianliang Gao, Jiamin Chen

  98. Sampling Enclosing Subgraphs for Link Prediction.

    Paul Louis, Shweta Ann Jacob, Amirali Salehi-Abari

  99. Urban Region Profiling via Multi-Graph Representation Learning.

    Yan Luo, Fu-Lai Chung, Kai Chen

  100. Improving Graph-based Document-Level Relation Extraction Model with Novel Graph Structure.

    Seongsik Park, Dongkeun Yoon, Harksoo Kim

  101. GRETEL: Graph Counterfactual Explanation Evaluation Framework.

    Mario Alfonso Prado-Romero, Giovanni Stilo

  102. Do Graph Neural Networks Build Fair User Models? Assessing Disparate Impact and Mistreatment in Behavioural User Profiling.

    Erasmo Purificato, Ludovico Boratto, Ernesto William De Luca

  103. Explainable Graph-based Fraud Detection via Neural Meta-graph Search.

    Zidi Qin, Yang Liu, Qing He, Xiang Ao

  104. A Model-Centric Explainer for Graph Neural Network based Node Classification.

    Sayan Saha, Monidipa Das, Sanghamitra Bandyopadhyay

  105. A Graph-based Spatiotemporal Model for Energy Markets.

    Swati Sharma, Srinivasan Iyengar, Shun Zheng, Kshitij Kapoor, Wei Cao, Jiang Bian, Shivkumar Kalyanaraman, John Lemmon

  106. ST-GAT: A Spatio-Temporal Graph Attention Network for Accurate Traffic Speed Prediction.

    Junho Song, Jiwon Son, Dong-hyuk Seo, Kyungsik Han, Namhyuk Kim, Sang-Wook Kim

  107. Multi-Aspect Embedding of Dynamic Graphs.

    Aimin Sun, Zhiguo Gong

  108. Leveraging the Graph Structure of Neural Network Training Dynamics.

    Fatemeh Vahedian, Ruiyu Li, Puja Trivedi, Di Jin, Danai Koutra

  109. Efficiently Answering Minimum Reachable Label Set Queries in Edge-Labeled Graphs.

    Yanping Wu, Renjie Sun, Chen Chen, Xiaoyang Wang, Xianming Fu

  110. Calibrate Automated Graph Neural Network via Hyperparameter Uncertainty.

    Xueying Yang, Jiamian Wang, Xujiang Zhao, Sheng Li, Zhiqiang Tao

  111. An Enhanced Gated Graph Neural Network for E-commerce Recommendation.

    Jihai Zhang, Fangquan Lin, Cheng Yang, Ziqiang Cui

  112. Graph Representation Learning via Adaptive Multi-layer Neighborhood Diffusion Contrast.

    Jijie Zhang, Yan Yang, Yong Liu, Meng Han, Shaowei Yin

  113. Deep Contrastive Multiview Network Embedding.

    Mengqi Zhang, Yanqiao Zhu, Qiang Liu, Shu Wu, Liang Wang

  114. SuGeR: A Subgraph-based Graph Convolutional Network Method for Bundle Recommendation.

    Zhenning Zhang, Boxin Du, Hanghang Tong

  115. KSG: Knowledge and Skill Graph.

    Feng Zhao, Ziqi Zhang, Donglin Wang

  116. Spherical Graph Embedding for Item Retrieval in Recommendation System.

    Wenqiao Zhu, Yesheng Xu, Xin Huang, Qiyang Min, Xun Zhou

  117. GALGO: Scalable Graph Analytics with a Parallel DBMS.

    Wellington Cabrera, Xiantian Zhou, Ladjel Bellatreche, Carlos Ordonez

  118. DASH: An Agile Knowledge Graph System Disentangling Demands, Algorithms, Data Resources, and Humans.

    Shaowei Chen, Haoran Wang, Jie Liu, Jiahui Wu

  119. A GPU-based Graph Pattern Mining System.

    Lin Hu, Lei Zou

  120. Flurry: A Fast Framework for Provenance Graph Generation for Representation Learning.

    Maya Kapoor, Joshua Melton, Michael Ridenhour, Thomas Moyer, Siddharth Krishnan

  121. Approximate and Interactive Processing of Aggregate Queries on Knowledge Graphs: A Demonstration.

    Yuxiang Wang, Arijit Khan, Xiaoliang Xu, Shuzhan Ye, Shihuang Pan, Yuhan Zhou

  122. gCBO: A Cost-based Optimizer for Graph Databases.

    Linglin Yang, Lei Yang, Yue Pang, Lei Zou

  123. ExeKG: Executable Knowledge Graph System for User-friendly Data Analytics.

    Zhuoxun Zheng, Baifan Zhou, Dongzhuoran Zhou, Ahmet Soylu, Evgeny Kharlamov

  124. ScheRe: Schema Reshaping for Enhancing Knowledge Graph Construction.

    Dongzhuoran Zhou, Baifan Zhou, Zhuoxun Zheng, Ahmet Soylu, Ognjen Savkovic, Egor V. Kostylev, Evgeny Kharlamov

  125. Fifty Shades of Pink: Understanding Color in e-commerce using Knowledge Graphs.

    Lizzie Liang, Sneha Kamath, Petar Ristoski, Qunzhi Zhou, Zhe Wu

  126. Shoe Size Resolution in Search Queries and Product Listings using Knowledge Graphs.

    Petar Ristoski, Aritra Mandal, Simon Becker, Anu Mandalam, Ethan Hart, Sanjika Hewavitharana, Zhe Wu, Qunzhi Zhou

  127. Geographical Address Models in the Indian e-Commerce.

    Ravindra Babu Tallamraju

  128. Executable Knowledge Graph for Transparent Machine Learning in Welding Monitoring at Bosch.

    Zhuoxun Zheng, Baifan Zhou, Dongzhuoran Zhou, Ahmet Soylu, Evgeny Kharlamov

  129. Causal Relationship over Knowledge Graphs.

    Hao Huang

  130. Graph-based Management and Mining of Blockchain Data.

    Arijit Khan, Cuneyt Gurcan Akcora

  131. Mining of Real-world Hypergraphs: Patterns, Tools, and Generators.

    Geon Lee, Jaemin Yoo, Kijung Shin

  132. TrustLOG: The First Workshop on Trustworthy Learning on Graphs.

    Jian Kang, Shuaicheng Zhang, Bo Li, Jingrui He, Jian Pei, Dawei Zhou

  133. The 1st International Workshop on Federated Learning with Graph Data (FedGraph).

    Carl Yang, Xiaoxiao Li, Nathalie Baracaldo, Neil Shah, Chaoyang He, Lingjuan Lyu, Lichao Sun, Salman Avestimehr

  1. SVGA-Net: Sparse Voxel-Graph Attention Network for 3D Object Detection from Point Clouds

    Qingdong He, Zhengning Wang, Hao Zeng, Yi Zeng, Yijun Liu

  2. Graph-Based Point Tracker for 3D Object Tracking in Point Clouds

    Minseong Park, Hongje Seong, Wonje Jang, Euntai Kim

  3. Learning to Detect 3D Facial Landmarks via Heatmap Regression with Graph Convolutional Network

    Yuan Wang, Min Cao, Zhenfeng Fan, Silong Peng

  4. Adaptive Hypergraph Neural Network for Multi-Person Pose Estimation

    Xixia Xu, Qi Zou, Xue Lin

  5. ACGNet: Action Complement Graph Network for Weakly-Supervised Temporal Action Localization

    Zichen Yang, Jie Qin, Di Huang

  6. Hybrid Graph Neural Networks for Few-Shot Learning

    Tianyuan Yu, Sen He, Yi-Zhe Song, Tao Xiang

  7. MAGIC: Multimodal relAtional Graph adversarIal inferenCe for Diverse and Unpaired Text-Based Image Captioning

    Wenqiao Zhang, Haochen Shi, Jiannan Guo, Shengyu Zhang, Qingpeng Cai, Juncheng Li, Sihui Luo, Yueting Zhuang

  8. Regularizing Graph Neural Networks via Consistency-Diversity Graph Augmentations

    Deyu Bo, Binbin Hu, Xiao Wang, Zhiqiang Zhang, Chuan Shi, Jun Zhou

  9. Differentially Describing Groups of Graphs

    Corinna Coupette, Sebastian Dalleiger, Jilles Vreeken

  10. Molecular Contrastive Learning with Chemical Element Knowledge Graph

    Yin Fang, Qiang Zhang, Haihong Yang, Xiang Zhuang, Shumin Deng, Wen Zhang, Ming Qin, Zhuo Chen, Xiaohui Fan, Huajun Chen

  11. Heterogeneity-Aware Twitter Bot Detection with Relational Graph Transformers

    Shangbin Feng, Zhaoxuan Tan, Rui Li, Minnan Luo

  12. Orthogonal Graph Neural Networks

    Kai Guo, Kaixiong Zhou, Xia Hu, Yu Li, Yi Chang, Xin Wang

  13. GNN-Retro: Retrosynthetic Planning with Graph Neural Networks

    Peng Han, Peilin Zhao, Chan Lu, Junzhou Huang, Jiaxiang Wu, Shuo Shang, Bin Yao, Xiangliang Zhang

  14. Block Modeling-Guided Graph Convolutional Neural Networks

    Dongxiao He, Chundong Liang, Huixin Liu, Mingxiang Wen, Pengfei Jiao, Zhiyong Feng

  15. From One to All: Learning to Match Heterogeneous and Partially Overlapped Graphs

    Weijie Liu, Hui Qian, Chao Zhang, Jiahao Xie, Zebang Shen, Nenggan Zheng

  16. TLogic: Temporal Logical Rules for Explainable Link Forecasting on Temporal Knowledge Graphs

    Yushan Liu, Yunpu Ma, Marcel Hildebrandt, Mitchell Joblin, Volker Tresp

  17. A Self-Supervised Mixed-Curvature Graph Neural Network

    Li Sun, Zhongbao Zhang, Junda Ye, Hao Peng, Jiawei Zhang, Sen Su, Philip S. Yu

  18. Graph Structure Learning with Variational Information Bottleneck

    Qingyun Sun, Jianxin Li, Hao Peng, Jia Wu, Xingcheng Fu, Cheng Ji, Philip S. Yu

  19. Exploring Relational Semantics for Inductive Knowledge Graph Completion

    Changjian Wang, Xiaofei Zhou, Shirui Pan, Linhua Dong, Zeliang Song, Ying Sha

  20. HAGEN: Homophily-Aware Graph Convolutional Recurrent Network for Crime Forecasting

    Chenyu Wang, Zongyu Lin, Xiaochen Yang, Jiao Sun, Mingxuan Yue, Cyrus Shahabi

  21. Powerful Graph Convolutional Networks with Adaptive Propagation Mechanism for Homophily and Heterophily

    Tao Wang, Di Jin, Rui Wang, Dongxiao He, Yuxiao Huang

  22. CoCoS: Enhancing Semi-supervised Learning on Graphs with Unlabeled Data via Contrastive Context Sharing

    Siyue Xie, Da Sun Handason Tam, Wing Cheong Lau

  23. Unsupervised Adversarially Robust Representation Learning on Graphs

    Jiarong Xu, Yang Yang, Junru Chen, Xin Jiang, Chunping Wang, Jiangang Lu, Yizhou Sun

  24. Blindfolded Attackers Still Threatening: Strict Black-Box Adversarial Attacks on Graphs

    Jiarong Xu, Yizhou Sun, Xin Jiang, Yanhao Wang, Chunping Wang, Jiangang Lu, Yang Yang

  25. Self-Supervised Graph Neural Networks via Diverse and Interactive Message Passing

    Liang Yang, Cheng Chen, Weixun Li, Bingxin Niu, Junhua Gu, Chuan Wang, Dongxiao He, Yuanfang Guo, Xiaochun Cao

  26. Multi-Scale Distillation from Multiple Graph Neural Networks

    Chunhai Zhang, Jie Liu, Kai Dang, Wenzheng Zhang

  27. Robust Heterogeneous Graph Neural Networks against Adversarial Attacks

    Mengmei Zhang, Xiao Wang, Meiqi Zhu, Chuan Shi, Zhiqiang Zhang, Jun Zhou

  28. Multi-View Intent Disentangle Graph Networks for Bundle Recommendation

    Sen Zhao, Wei Wei, Ding Zou, Xianling Mao

  29. Defending Graph Convolutional Networks against Dynamic Graph Perturbations via Bayesian Self-Supervision

    Jun Zhuang, Mohammad Al Hasan

  30. GeomGCL: Geometric Graph Contrastive Learning for Molecular Property Prediction

    Shuangli Li, Jingbo Zhou, Tong Xu, Dejing Dou, Hui Xiong

  31. Context-Aware Health Event Prediction via Transition Functions on Dynamic Disease Graphs

    Chang Lu, Tian Han, Yue Ning

  32. DDGCN: Dual Dynamic Graph Convolutional Networks for Rumor Detection on Social Media

    Mengzhu Sun, Xi Zhang, Jiaqi Zheng, Guixiang Ma

  33. RepBin: Constraint-Based Graph Representation Learning for Metagenomic Binning

    Hansheng Xue, Vijini Mallawaarachchi, Yujia Zhang, Vaibhav Rajan, Yu Lin

  34. ZINB-Based Graph Embedding Autoencoder for Single-Cell RNA-Seq Interpretations

    Zhuohan Yu, Yifu Lu, Yunhe Wang, Fan Tang, Ka-Chun Wong, Xiangtao Li

  35. Hierarchical Multi-Supervision Multi-Interaction Graph Attention Network for Multi-Camera Pedestrian Trajectory Prediction

    Guoliang Zhao, Yuxun Zhou, Zhanbo Xu, Yadong Zhou, Jiang Wu

  36. ER: Equivariance Regularizer for Knowledge Graph Completion

    Zongsheng Cao, Qianqian Xu, Zhiyong Yang, Qingming Huang

  37. Geometry Interaction Knowledge Graph Embeddings

    Zongsheng Cao, Qianqian Xu, Zhiyong Yang, Xiaochun Cao, Qingming Huang

  38. Multi-Relational Graph Representation Learning with Bayesian Gaussian Process Network

    Guanzheng Chen, Jinyuan Fang, Zaiqiao Meng, Qiang Zhang, Shangsong Liang

  39. How Does Knowledge Graph Embedding Extrapolate to Unseen Data: A Semantic Evidence View

    Ren Li, Yanan Cao, Qiannan Zhu, Guanqun Bi, Fang Fang, Yi Liu, Qian Li

  40. Multi-View Graph Representation for Programming Language Processing: An Investigation into Algorithm Detection

    Ting Long, Yutong Xie, Xianyu Chen, Weinan Zhang, Qinxiang Cao, Yong Yu

  41. TempoQR: Temporal Question Reasoning over Knowledge Graphs

    Costas Mavromatis, Prasanna Lakkur Subramanyam, Vassilis N. Ioannidis, Adesoji Adeshina, Phillip R. Howard, Tetiana Grinberg, Nagib Hakim, George Karypis

  42. Learning to Walk with Dual Agents for Knowledge Graph Reasoning

    Denghui Zhang, Zixuan Yuan, Hao Liu, Xiaodong Lin, Hui Xiong

  43. Beyond GNNs: An Efficient Architecture for Graph Problems

    Pranjal Awasthi, Abhimanyu Das, Sreenivas Gollapudi

  44. Graph Neural Controlled Differential Equations for Traffic Forecasting

    Jeongwhan Choi, Hwangyong Choi, Jeehyun Hwang, Noseong Park

  45. Graph-Wise Common Latent Factor Extraction for Unsupervised Graph Representation Learning

    Thilini Cooray, Ngai-Man Cheung

  46. Meta Propagation Networks for Graph Few-shot Semi-supervised Learning

    Kaize Ding, Jianling Wang, James Caverlee, Huan Liu

  47. Disentangled Spatiotemporal Graph Generative Models

    Yuanqi Du, Xiaojie Guo, Hengning Cao, Yanfang Ye, Liang Zhao

  48. Learning from the Dark: Boosting Graph Convolutional Neural Networks with Diverse Negative Samples

    Wei Duan, Junyu Xuan, Maoying Qiao, Jie Lu

  49. KerGNNs: Interpretable Graph Neural Networks with Graph Kernels

    Aosong Feng, Chenyu You, Shiqiang Wang, Leandros Tassiulas

  50. LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks

    Adam Goodge, Bryan Hooi, See-Kiong Ng, Wee Siong Ng

  51. TIGGER: Scalable Generative Modelling for Temporal Interaction Graphs

    Shubham Gupta, Sahil Manchanda, Srikanta Bedathur, Sayan Ranu

  52. Cross-Domain Few-Shot Graph Classification

    Kaveh Hassani

  53. SpreadGNN: Decentralized Multi-Task Federated Learning for Graph Neural Networks on Molecular Data

    Chaoyang He, Emir Ceyani, Keshav Balasubramanian, Murali Annavaram, Salman Avestimehr

  54. Fast Graph Neural Tangent Kernel via Kronecker Sketching

    Shunhua Jiang, Yunze Man, Zhao Song, Zheng Yu, Danyang Zhuo

  55. Adaptive Kernel Graph Neural Network

    Mingxuan Ju, Shifu Hou, Yujie Fan, Jianan Zhao, Yanfang Ye, Liang Zhao

  56. Directed Graph Auto-Encoders

    Georgios Kollias, Vasileios Kalantzis, Tsuyoshi Idé, Aurélie C. Lozano, Naoki Abe

  57. Augmentation-Free Self-Supervised Learning on Graphs

    Namkyeong Lee, Junseok Lee, Chanyoung Park

  58. Robust Graph-Based Multi-View Clustering

    Weixuan Liang, Xinwang Liu, Sihang Zhou, Jiyuan Liu, Siwei Wang, En Zhu

  59. On the Use of Unrealistic Predictions in Hundreds of Papers Evaluating Graph Representations

    Li-Chung Lin, Cheng-Hung Liu, Chih-Ming Chen, Kai-Chin Hsu, I-Feng Wu, Ming-Feng Tsai, Chih-Jen Lin

  60. Graph Convolutional Networks with Dual Message Passing for Subgraph Isomorphism Counting and Matching

    Xin Liu, Yangqiu Song

  61. Deep Graph Clustering via Dual Correlation Reduction

    Yue Liu, Wenxuan Tu, Sihang Zhou, Xinwang Liu, Linxuan Song, Xihong Yang, En Zhu

  62. fGOT: Graph Distances Based on Filters and Optimal Transport

    Hermina Petric Maretic, Mireille El Gheche, Giovanni Chierchia, Pascal Frossard

  63. Temporal Knowledge Graph Completion Using Box Embeddings

    Johannes Messner, Ralph Abboud, Ismail Ilkan Ceylan

  64. Simple Unsupervised Graph Representation Learning

    Yujie Mo, Liang Peng, Jie Xu, Xiaoshuang Shi, Xiaofeng Zhu

  65. Bag Graph: Multiple Instance Learning Using Bayesian Graph Neural Networks

    Soumyasundar Pal, Antonios Valkanas, Florence Regol, Mark Coates

  66. Deformable Graph Convolutional Networks

    Jinyoung Park, Sungdong Yoo, Jihwan Park, Hyunwoo J. Kim

  67. Graph Transplant: Node Saliency-Guided Graph Mixup with Local Structure Preservation

    Joonhyung Park, Hajin Shim, Eunho Yang

  68. Interpretable Neural Subgraph Matching for Graph Retrieval

    Indradyumna Roy, Venkata Sai Baba Reddy Velugoti, Soumen Chakrabarti, Abir De

  69. Hypergraph Modeling via Spectral Embedding Connection: Hypergraph Cut, Weighted Kernel k-Means, and Heat Kernel

    Shota Saito

  70. VACA: Designing Variational Graph Autoencoders for Causal Queries

    Pablo Sánchez-Martín, Miriam Rateike, Isabel Valera

  71. Graph Filtration Kernels

    Till Hendrik Schulz, Pascal Welke, Stefan Wrobel

  72. EqGNN: Equalized Node Opportunity in Graphs

    Uriel Singer, Kira Radinsky

  73. Graph Pointer Neural Networks

    Tianmeng Yang, Yujing Wang, Zhihan Yue, Yaming Yang, Yunhai Tong, Jing Bai

  74. AutoGCL: Automated Graph Contrastive Learning via Learnable View Generators

    Yihang Yin, Qingzhong Wang, Siyu Huang, Haoyi Xiong, Xiang Zhang

  75. Early-Bird GCNs: Graph-Network Co-optimization towards More Efficient GCN Training and Inference via Drawing Early-Bird Lottery Tickets

    Haoran You, Zhihan Lu, Zijian Zhou, Yonggan Fu, Yingyan Lin

  76. SAIL: Self-Augmented Graph Contrastive Learning

    Lu Yu, Shichao Pei, Lizhong Ding, Jun Zhou, Longfei Li, Chuxu Zhang, Xiangliang Zhang

  77. Low-Pass Graph Convolutional Network for Recommendation

    Wenhui Yu, Zixin Zhang, Zheng Qin

  78. Batch Active Learning with Graph Neural Networks via Multi-Agent Deep Reinforcement Learning

    Yuheng Zhang, Hanghang Tong, Yinglong Xia, Yan Zhu, Yuejie Chi, Lei Ying

  79. ProtGNN: Towards Self-Explaining Graph Neural Networks

    Zaixi Zhang, Qi Liu, Hao Wang, Chengqiang Lu, Cheekong Lee

  80. Structural Landmarking and Interaction Modelling: A "SLIM" Network for Graph Classification

    Yaokang Zhu, Kai Zhang, Jun Wang, Haibin Ling, Jie Zhang, Hongyuan Zha

  81. Practical Fixed-Parameter Algorithms for Defending Active Directory Style Attack Graphs

    Mingyu Guo, Jialiang Li, Aneta Neumann, Frank Neumann, Hung Nguyen

  82. Solving Disjunctive Temporal Networks with Uncertainty under Restricted Time-Based Controllability Using Tree Search and Graph Neural Networks

    Kevin Osanlou, Jeremy Frank, Andrei Bursuc, Tristan Cazenave, Eric Jacopin, Christophe Guettier, J. Benton

  83. Qubit Routing Using Graph Neural Network Aided Monte Carlo Tree Search

    Animesh Sinha, Utkarsh Azad, Harjinder Singh

  84. Enhanced Story Comprehension for Large Language Models through Dynamic Document-Based Knowledge Graphs

    Berkeley R. Andrus, Yeganeh Nasiri, Shilong Cui, Benjamin Cullen, Nancy Fulda

  85. ISEEQ: Information Seeking Question Generation Using Dynamic Meta-Information Retrieval and Knowledge Graphs

    Manas Gaur, Kalpa Gunaratna, Vijay Srinivasan, Hongxia Jin

  86. Dynamic Key-Value Memory Enhanced Multi-Step Graph Reasoning for Knowledge-Based Visual Question Answering

    Mingxiao Li, Marie-Francine Moens

  87. LeSICiN: A Heterogeneous Graph-Based Approach for Automatic Legal Statute Identification from Indian Legal Documents

    Shounak Paul, Pawan Goyal, Saptarshi Ghosh

  88. Sparse Structure Learning via Graph Neural Networks for Inductive Document Classification

    Yinhua Piao, Sangseon Lee, Dohoon Lee, Sun Kim

  89. Hierarchical Heterogeneous Graph Attention Network for Syntax-Aware Summarization

    Zixing Song, Irwin King

  90. DisenCite: Graph-Based Disentangled Representation Learning for Context-Specific Citation Generation

    Yifan Wang, Yiping Song, Shuai Li, Chaoran Cheng, Wei Ju, Ming Zhang, Sheng Wang

  91. GraphMemDialog: Optimizing End-to-End Task-Oriented Dialog Systems Using Graph Memory Networks

    Jie Wu, Ian G. Harris, Hongzhi Zhao

  92. A Graph Convolutional Network with Adaptive Graph Generation and Channel Selection for Event Detection

    Zhipeng Xie, Yumin Tu

  93. JAKET: Joint Pre-training of Knowledge Graph and Language Understanding

    Donghan Yu, Chenguang Zhu, Yiming Yang, Michael Zeng

  94. CausalGNN: Causal-Based Graph Neural Networks for Spatio-Temporal Epidemic Forecasting

    Lijing Wang, Aniruddha Adiga, Jiangzhuo Chen, Adam Sadilek, Srinivasan Venkatramanan, Madhav V. Marathe

  95. Accelerating COVID-19 Research with Graph Mining and Transformer-Based Learning

    Ilya Tyagin, Ankit Kulshrestha, Justin Sybrandt, Krish Matta, Michael Shtutman, Ilya Safro

  1. A New Perspective on "How Graph Neural Networks Go Beyond Weisfeiler-Lehman?".

    Asiri Wijesinghe, Qing Wang

  2. Data-Efficient Graph Grammar Learning for Molecular Generation.

    Minghao Guo, Veronika Thost, Beichen Li, Payel Das, Jie Chen, Wojciech Matusik

  3. Expressiveness and Approximation Properties of Graph Neural Networks.

    Floris Geerts, Juan L. Reutter

  4. Understanding over-squashing and bottlenecks on graphs via curvature.

    Jake Topping, Francesco Di Giovanni, Benjamin Paul Chamberlain, Xiaowen Dong, Michael M. Bronstein

  5. Is Homophily a Necessity for Graph Neural Networks?

    Yao Ma, Xiaorui Liu, Neil Shah, Jiliang Tang

  6. DEGREE: Decomposition Based Explanation for Graph Neural Networks.

    Qizhang Feng, Ninghao Liu, Fan Yang, Ruixiang Tang, Mengnan Du, Xia Hu

  7. Towards Training Billion Parameter Graph Neural Networks for Atomic Simulations.

    Anuroop Sriram, Abhishek Das, Brandon M. Wood, Siddharth Goyal, C. Lawrence Zitnick

  8. On Evaluation Metrics for Graph Generative Models.

    Rylee Thompson, Boris Knyazev, Elahe Ghalebi, Jungtaek Kim, Graham W. Taylor

  9. Graph Condensation for Graph Neural Networks.

    Wei Jin, Lingxiao Zhao, Shichang Zhang, Yozen Liu, Jiliang Tang, Neil Shah

  10. From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness.

    Lingxiao Zhao, Wei Jin, Leman Akoglu, Neil Shah

  11. Triangle and Four Cycle Counting with Predictions in Graph Streams.

    Justin Y. Chen, Talya Eden, Piotr Indyk, Honghao Lin, Shyam Narayanan, Ronitt Rubinfeld, Sandeep Silwal, Tal Wagner, David P. Woodruff, Michael Zhang

  12. NodePiece: Compositional and Parameter-Efficient Representations of Large Knowledge Graphs.

    Mikhail Galkin, Etienne G. Denis, Jiapeng Wu, William L. Hamilton

  13. Graphon based Clustering and Testing of Networks: Algorithms and Theory.

    Mahalakshmi Sabanayagam, Leena Chennuru Vankadara, Debarghya Ghoshdastidar

  14. How Attentive are Graph Attention Networks?

    Shaked Brody, Uri Alon, Eran Yahav

  15. Graph-less Neural Networks: Teaching Old MLPs New Tricks Via Distillation.

    Shichang Zhang, Yozen Liu, Yizhou Sun, Neil Shah

  16. Large-Scale Representation Learning on Graphs via Bootstrapping.

    Shantanu Thakoor, Corentin Tallec, Mohammad Gheshlaghi Azar, Mehdi Azabou, Eva L. Dyer, Rémi Munos, Petar Velickovic, Michal Valko

  17. Top-N: Equivariant Set and Graph Generation without Exchangeability.

    Clément Vignac, Pascal Frossard

  18. PF-GNN: Differentiable particle filtering based approximation of universal graph representations.

    Mohammed Haroon Dupty, Yanfei Dong, Wee Sun Lee

  19. Equivariant Graph Mechanics Networks with Constraints.

    Wenbing Huang, Jiaqi Han, Yu Rong, Tingyang Xu, Fuchun Sun, Junzhou Huang

  20. Convergent Graph Solvers.

    Junyoung Park, Jinhyun Choo, Jinkyoo Park

  21. GLASS: GNN with Labeling Tricks for Subgraph Representation Learning.

    Xiyuan Wang, Muhan Zhang

  22. Space-Time Graph Neural Networks.

    Samar Hadou, Charilaos I. Kanatsoulis, Alejandro Ribeiro

  23. End-to-End Learning of Probabilistic Hierarchies on Graphs.

    Daniel Zügner, Bertrand Charpentier, Morgane Ayle, Sascha Geringer, Stephan Günnemann

  24. GraphENS: Neighbor-Aware Ego Network Synthesis for Class-Imbalanced Node Classification.

    Joonhyung Park, Jaeyun Song, Eunho Yang

  25. Why Propagate Alone? Parallel Use of Labels and Features on Graphs.

    Yangkun Wang, Jiarui Jin, Weinan Zhang, Yongyi Yang, Jiuhai Chen, Quan Gan, Yong Yu, Zheng Zhang, Zengfeng Huang, David Wipf

  26. Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks.

    Haorui Wang, Haoteng Yin, Muhan Zhang, Pan Li

  27. Query Embedding on Hyper-Relational Knowledge Graphs.

    Dimitrios Alivanistos, Max Berrendorf, Michael Cochez, Mikhail Galkin

  28. Inductive Relation Prediction Using Analogy Subgraph Embeddings.

    Jiarui Jin, Yangkun Wang, Kounianhua Du, Weinan Zhang, Zheng Zhang, David Wipf, Yong Yu, Quan Gan

  29. Graph Neural Network Guided Local Search for the Traveling Salesperson Problem.

    Benjamin Hudson, Qingbiao Li, Matthew Malencia, Amanda Prorok

  30. Understanding and Improving Graph Injection Attack by Promoting Unnoticeability.

    Yongqiang Chen, Han Yang, Yonggang Zhang, Kaili Ma, Tongliang Liu, Bo Han, James Cheng

  31. Self-Supervised Graph Neural Networks for Improved Electroencephalographic Seizure Analysis.

    Siyi Tang, Jared Dunnmon, Khaled Kamal Saab, Xuan Zhang, Qianying Huang, Florian Dubost, Daniel L. Rubin, Christopher Lee-Messer

  32. EXACT: Scalable Graph Neural Networks Training via Extreme Activation Compression.

    Zirui Liu, Kaixiong Zhou, Fan Yang, Li Li, Rui Chen, Xia Hu

  33. Graph-Relational Domain Adaptation.

    Zihao Xu, Hao He, Guang-He Lee, Bernie Wang, Hao Wang

  34. PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication.

    Cheng Wan, Youjie Li, Cameron R. Wolfe, Anastasios Kyrillidis, Nam Sung Kim, Yingyan Lin

  35. Graph Neural Networks with Learnable Structural and Positional Representations.

    Vijay Prakash Dwivedi, Anh Tuan Luu, Thomas Laurent, Yoshua Bengio, Xavier Bresson

  36. Graph Auto-Encoder via Neighborhood Wasserstein Reconstruction.

    Mingyue Tang, Pan Li, Carl Yang

  37. Towards Deepening Graph Neural Networks: A GNTK-based Optimization Perspective.

    Wei Huang, Yayong Li, Weitao Du, Richard Y. D. Xu, Jie Yin, Ling Chen, Miao Zhang

  38. Learn Locally, Correct Globally: A Distributed Algorithm for Training Graph Neural Networks.

    Morteza Ramezani, Weilin Cong, Mehrdad Mahdavi, Mahmut T. Kandemir, Anand Sivasubramaniam

  39. Neural Methods for Logical Reasoning over Knowledge Graphs.

    Alfonso Amayuelas, Shuai Zhang, Susie Xi Rao, Ce Zhang

  40. Graph-Guided Network for Irregularly Sampled Multivariate Time Series.

    Xiang Zhang, Marko Zeman, Theodoros Tsiligkaridis, Marinka Zitnik

  41. Explainable GNN-Based Models over Knowledge Graphs.

    David Jaime Tena Cucala, Bernardo Cuenca Grau, Egor V. Kostylev, Boris Motik

  42. Pre-training Molecular Graph Representation with 3D Geometry.

    Shengchao Liu, Hanchen Wang, Weiyang Liu, Joan Lasenby, Hongyu Guo, Jian Tang

  43. GRAND++: Graph Neural Diffusion with A Source Term.

    Matthew Thorpe, Tan Minh Nguyen, Hedi Xia, Thomas Strohmer, Andrea L. Bertozzi, Stanley J. Osher, Bao Wang

  44. Semi-relaxed Gromov-Wasserstein divergence and applications on graphs.

    Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli, Titouan Vayer, Nicolas Courty

  45. Using Graph Representation Learning with Schema Encoders to Measure the Severity of Depressive Symptoms.

    Simin Hong, Anthony G. Cohn, David Crossland Hogg

  46. Learning Graphon Mean Field Games and Approximate Nash Equilibria.

    Kai Cui, Heinz Koeppl

  47. Topological Graph Neural Networks.

    Max Horn, Edward De Brouwer, Michael Moor, Yves Moreau, Bastian Rieck, Karsten M. Borgwardt

  48. Automated Self-Supervised Learning for Graphs.

    Wei Jin, Xiaorui Liu, Xiangyu Zhao, Yao Ma, Neil Shah, Jiliang Tang

  49. You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks.

    Eli Chien, Chao Pan, Jianhao Peng, Olgica Milenkovic

  50. Cold Brew: Distilling Graph Node Representations with Incomplete or Missing Neighborhoods.

    Wenqing Zheng, Edward W. Huang, Nikhil Rao, Sumeet Katariya, Zhangyang Wang, Karthik Subbian

  51. Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery.

    Yulun Wu, Nicholas Choma, Andrew Deru Chen, Mikaela Cashman, Érica Teixeira Prates, Verónica G. Melesse Vergara, Manesh Shah, Austin Clyde, Thomas S. Brettin, Wibe Albert de Jong, Neeraj Kumar, Martha S. Head, Rick L. Stevens, Peter Nugent, Daniel A. Jacobson, James B. Brown

  52. Spherical Message Passing for 3D Molecular Graphs.

    Yi Liu, Limei Wang, Meng Liu, Yuchao Lin, Xuan Zhang, Bora Oztekin, Shuiwang Ji

  53. Fairness Guarantees under Demographic Shift.

    Stephen Giguere, Blossom Metevier, Bruno Castro da Silva, Yuriy Brun, Philip S. Thomas, Scott Niekum

  54. Learning Guarantees for Graph Convolutional Networks on the Stochastic Block Model.

    Wei Lu

  55. Graph-based Nearest Neighbor Search in Hyperbolic Spaces.

    Liudmila Prokhorenkova, Dmitry Baranchuk, Nikolay Bogachev, Yury Demidovich, Alexander Kolpakov

  56. Discovering Invariant Rationales for Graph Neural Networks.

    Yingxin Wu, Xiang Wang, An Zhang, Xiangnan He, Tat-Seng Chua

  57. Do We Need Anisotropic Graph Neural Networks?

    Shyam A. Tailor, Felix L. Opolka, Pietro Liò, Nicholas Donald Lane

  58. Simple GNN Regularisation for 3D Molecular Property Prediction and Beyond.

    Jonathan Godwin, Michael Schaarschmidt, Alexander L. Gaunt, Alvaro Sanchez-Gonzalez, Yulia Rubanova, Petar Velickovic, James Kirkpatrick, Peter W. Battaglia

  59. Filling the G_ap_s: Multivariate Time Series Imputation by Graph Neural Networks.

    Andrea Cini, Ivan Marisca, Cesare Alippi

  60. Information Gain Propagation: a New Way to Graph Active Learning with Soft Labels.

    Wentao Zhang, Yexin Wang, Zhenbang You, Meng Cao, Ping Huang, Jiulong Shan, Zhi Yang, Bin Cui

  61. Handling Distribution Shifts on Graphs: An Invariance Perspective.

    Qitian Wu, Hengrui Zhang, Junchi Yan, David Wipf

  62. Generalized Demographic Parity for Group Fairness.

    Zhimeng Jiang, Xiaotian Han, Chao Fan, Fan Yang, Ali Mostafavi, Xia Hu

  63. Fixed Neural Network Steganography: Train the images, not the network.

    Varsha Kishore, Xiangyu Chen, Yan Wang, Boyi Li, Kilian Q. Weinberger

  64. A Biologically Interpretable Graph Convolutional Network to Link Genetic Risk Pathways and Imaging Phenotypes of Disease.

    Sayan Ghosal, Qiang Chen, Giulio Pergola, Aaron L. Goldman, William Ulrich, Daniel R. Weinberger, Archana Venkataraman

  65. Retriever: Learning Content-Style Representation as a Token-Level Bipartite Graph.

    Dacheng Yin, Xuanchi Ren, Chong Luo, Yuwang Wang, Zhiwei Xiong, Wenjun Zeng

  66. GNN is a Counter? Revisiting GNN for Question Answering.

    Kuan Wang, Yuyu Zhang, Diyi Yang, Le Song, Tao Qin

  67. Neural graphical modelling in continuous-time: consistency guarantees and algorithms.

    Alexis Bellot, Kim Branson, Mihaela van der Schaar

  68. Learning to Schedule Learning rate with Graph Neural Networks.

    Yuanhao Xiong, Li-Cheng Lan, Xiangning Chen, Ruochen Wang, Cho-Jui Hsieh

  69. GreaseLM: Graph REASoning Enhanced Language Models.

    Xikun Zhang, Antoine Bosselut, Michihiro Yasunaga, Hongyu Ren, Percy Liang, Christopher D. Manning, Jure Leskovec

  70. Does your graph need a confidence boost? Convergent boosted smoothing on graphs with tabular node features.

    Jiuhai Chen, Jonas Mueller, Vassilis N. Ioannidis, Soji Adeshina, Yangkun Wang, Tom Goldstein, David Wipf

  71. TAMP-S2GCNets: Coupling Time-Aware Multipersistence Knowledge Representation with Spatio-Supra Graph Convolutional Networks for Time-Series Forecasting.

    Yuzhou Chen, Ignacio Segovia-Dominguez, Baris Coskunuzer, Yulia R. Gel

  72. GNN-LM: Language Modeling based on Global Contexts via GNN.

    Yuxian Meng, Shi Zong, Xiaoya Li, Xiaofei Sun, Tianwei Zhang, Fei Wu, Jiwei Li

  73. Revisiting Over-smoothing in BERT from the Perspective of Graph.

    Han Shi, Jiahui Gao, Hang Xu, Xiaodan Liang, Zhenguo Li, Lingpeng Kong, Stephen M. S. Lee, James T. Kwok

  74. Graph-Augmented Normalizing Flows for Anomaly Detection of Multiple Time Series.

    Enyan Dai, Jie Chen

  75. Iterative Refinement Graph Neural Network for Antibody Sequence-Structure Co-design.

    Wengong Jin, Jeremy Wohlwend, Regina Barzilay, Tommi S. Jaakkola

  76. Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave Functions.

    Nicholas Gao, Stephan Günnemann

  77. Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions.

    Leslie O'Bray, Max Horn, Bastian Rieck, Karsten M. Borgwardt

  78. Context-Aware Sparse Deep Coordination Graphs.

    Tonghan Wang, Liang Zeng, Weijun Dong, Qianlan Yang, Yang Yu, Chongjie Zhang

  79. Spanning Tree-based Graph Generation for Molecules.

    Sungsoo Ahn, Binghong Chen, Tianzhe Wang, Le Song

  80. Equivariant Subgraph Aggregation Networks.

    Beatrice Bevilacqua, Fabrizio Frasca, Derek Lim, Balasubramaniam Srinivasan, Chen Cai, Gopinath Balamurugan, Michael M. Bronstein, Haggai Maron

  1. Graph Collaborative Reasoning

    Hanxiong Chen, Yunqi Li, Shaoyun Shi, Shuchang Liu, He Zhu, Yongfeng Zhang

  2. Modeling Scale-free Graphs with Hyperbolic Geometry for Knowledge-aware Recommendation

    Yankai Chen, Menglin Yang, Yingxue Zhang, Mengchen Zhao, Ziqiao Meng, Jianye Hao, Irwin King

  3. Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels

    Enyan Dai, Wei Jin, Hui Liu, Suhang Wang

  4. Predicting Human Mobility via Graph Convolutional Dual-attentive Networks

    Weizhen Dang, Haibo Wang, Shirui Pan, Pei Zhang, Chuan Zhou, Xin Chen, Jilong Wang

  5. Efficient Graph Convolution for Joint Node Representation Learning and Clustering

    Chakib Fettal, Lazhar Labiod, Mohamed Nadif

  6. HeteroQA: Learning towards Question-and-Answering through Multiple Information Sources via Heterogeneous Graph Modeling

    Shen Gao, Yuchi Zhang, Yongliang Wang, Yang Dong, Xiuying Chen, Dongyan Zhao, Rui Yan

  7. Multi-Scale Variational Graph AutoEncoder for Link Prediction

    Zhihao Guo, Feng Wang, Kaixuan Yao, Jiye Liang, Zhiqiang Wang

  8. Outside In: Market-aware Heterogeneous Graph Neural Network for Employee Turnover Prediction

    Jinquan Hang, Zheng Dong, Hongke Zhao, Xin Song, Peng Wang, Hengshu Zhu

  9. Triangle Graph Interest Network for Click-through Rate Prediction

    Wensen Jiang, Yizhu Jiao, Qingqin Wang, Chuanming Liang, Lijie Guo, Yao Zhang, Zhijun Sun, Yun Xiong, Yangyong Zhu

  10. KGNN: Harnessing Kernel-based Networks for Semi-supervised Graph Classification

    Wei Ju, Junwei Yang, Meng Qu, Weiping Song, Jianhao Shen, Ming Zhang

  11. GAGE: Geometry Preserving Attributed Graph Embeddings

    Charilaos I. Kanatsoulis, Nicholas D. Sidiropoulos

  12. Graph Embedding with Hierarchical Attentive Membership

    Lu Lin, Ethan Blaser, Hongning Wang

  13. Surrogate Representation Learning with Isometric Mapping for Gray-box Graph Adversarial Attacks

    Zihan Liu, Yun Luo, Zelin Zang, Stan Z. Li

  14. Ada-GNN: Adapting to Local Patterns for Improving Graph Neural Networks

    Zihan Luo, Jianxun Lian, Hong Huang, Hai Jin, Xing Xie

  15. ComGA: Community-Aware Attributed Graph Anomaly Detection

    Xuexiong Luo, Jia Wu, Amin Beheshti, Jian Yang, Xiankun Zhang, Yuan Wang, Shan Xue

  16. Learning Fair Node Representations with Graph Counterfactual Fairness

    Jing Ma, Ruocheng Guo, Mengting Wan, Longqi Yang, Aidong Zhang, Jundong Li

  17. Deep Graph-level Anomaly Detection by Glocal Knowledge Distillation

    Rongrong Ma, Guansong Pang, Ling Chen, Anton van den Hengel

  18. Heterogeneous Global Graph Neural Networks for Personalized Session-based Recommendation

    Yitong Pang, Lingfei Wu, Qi Shen, Yiming Zhang, Zhihua Wei, Fangli Xu, Ethan Chang, Bo Long, Jian Pei

  19. EvoKG: Jointly Modeling Event Time and Network Structure for Reasoning over Temporal Knowledge Graphs

    Namyong Park, Fuchen Liu, Purvanshi Mehta, Dana Cristofor, Christos Faloutsos, Yuxiao Dong

  20. Attributed Graph Modeling with Vertex Replacement Grammars

    Satyaki Sikdar, Neil Shah, Tim Weninger

  21. Graph Few-shot Class-incremental Learning

    Zhen Tan, Kaize Ding, Ruocheng Guo, Huan Liu

  22. Friend Story Ranking with Edge-Contextual Local Graph Convolutions

    Xianfeng Tang, Yozen Liu, Xinran He, Suhang Wang, Neil Shah

  23. Scalable Graph Topology Learning via Spectral Densification

    Yongyu Wang, Zhiqiang Zhao, Zhuo Feng

  24. Profiling the Design Space for Graph Neural Networks based Collaborative Filtering

    Zhenyi Wang, Huan Zhao, Chuan Shi

  25. Interpretable Relation Learning on Heterogeneous Graphs

    Qiang Yang, Qiannan Zhang, Chuxu Zhang, Xiangliang Zhang

  26. Bringing Your Own View: Graph Contrastive Learning without Prefabricated Data Augmentations

    Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen

  27. Community Trend Prediction on Heterogeneous Graph in E-commerce

    Jiahao Yuan, Zhao Li, Pengcheng Zou, Xuan Gao, Jinwei Pan, Wendi Ji, Xiaoling Wang

  28. Learning Concept Prerequisite Relations from Educational Data via Multi-Head Attention Variational Graph Auto-Encoders

    Juntao Zhang, Nanzhou Lin, Xuelong Zhang, Wei Song, Xiandi Yang, Zhiyong Peng

  29. Joint Learning of E-commerce Search and Recommendation with a Unified Graph Neural Network

    Kai Zhao, Yukun Zheng, Tao Zhuang, Xiang Li, Xiaoyi Zeng

  30. DualDE: Dually Distilling Knowledge Graph Embedding for Faster and Cheaper Reasoning

    Yushan Zhu, Wen Zhang, Mingyang Chen, Hui Chen, Xu Cheng, Wei Zhang, Huajun Chen

  31. A Neighborhood-Attention Fine-grained Entity Typing for Knowledge Graph Completion

    Jianhuan Zhuo, Qiannan Zhu, Yinliang Yue, Yuhong Zhao, Weisi Han

  1. Modeling User Behavior with Graph Convolution for Personalized Product Search

    Lu Fan, Qimai Li, Bo Liu, Xiao-Ming Wu, Xiaotong Zhang, Fuyu Lv, Guli Lin, Sen Li, Taiwei Jin, Keping Yang

  2. IHGNN: Interactive Hypergraph Neural Network for Personalized Product Search

    Dian Cheng, Jiawei Chen, Wenjun Peng, Wenqin Ye, Fuyu Lv, Tao Zhuang, Xiaoyi Zeng, Xiangnan He

  3. Efficient and Effective Similarity Search over Bipartite Graphs

    Renchi Yang

  4. RETE: Retrieval-Enhanced Temporal Event Forecasting on Unified Query Product Evolutionary Graph

    Ruijie Wang, Zheng Li, Danqing Zhang, Qingyu Yin, Tong Zhao, Bing Yin, Tarek F. Abdelzaher

  5. TTAGN: Temporal Transaction Aggregation Graph Network for Ethereum Phishing Scams Detection

    Sijia Li, Gaopeng Gou, Chang Liu, Chengshang Hou, Zhenzhen Li, Gang Xiong

  6. ALLIE: Active Learning on Large-scale Imbalanced Graphs

    Limeng Cui, Xianfeng Tang, Sumeet Katariya, Nikhil Rao, Pallav Agrawal, Karthik Subbian, Dongwon Lee

  7. Rethinking Graph Convolutional Networks in Knowledge Graph Completion

    Zhanqiu Zhang, Jie Wang, Jieping Ye, Feng Wu

  8. Swift and Sure: Hardness-aware Contrastive Learning for Low-dimensional Knowledge Graph Embeddings

    Kai Wang, Yu Liu, Quan Z. Sheng

  9. SelfKG: Self-Supervised Entity Alignment in Knowledge Graphs

    Xiao Liu, Haoyun Hong, Xinghao Wang, Zeyi Chen, Evgeny Kharlamov, Yuxiao Dong, Jie Tang

  10. Knowledge Graph Reasoning with Relational Digraph

    Yongqi Zhang, Quanming Yao

  11. Path Language Modeling over Knowledge Graphs for Explainable Recommendation

    Shijie Geng, Zuohui Fu, Juntao Tan, Yingqiang Ge, Gerard de Melo, Yongfeng Zhang

  12. Trustworthy Knowledge Graph Completion Based on Multi-sourced Noisy Data

    Jiacheng Huang, Yao Zhao, Wei Hu, Zhen Ning, Qijin Chen, Xiaoxia Qiu, Chengfu Huo, Weijun Ren

  13. Can Machine Translation be a Reasonable Alternative for Multilingual Question Answering Systems over Knowledge Graphs

    Aleksandr Perevalov, Andreas Both, Dennis Diefenbach, Axel-Cyrille Ngonga Ngomo

  14. Learning and Evaluating Graph Neural Network Explanations based on Counterfactual and Factual Reasoning

    Juntao Tan, Shijie Geng, Zuohui Fu, Yingqiang Ge, Shuyuan Xu, Yunqi Li, Yongfeng Zhang

  15. An Invertible Graph Diffusion Neural Network for Source Localization

    Junxiang Wang, Junji Jiang, Liang Zhao

  16. SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation

    Jun Xia, Lirong Wu, Jintao Chen, Bozhen Hu, Stan Z. Li

  17. MiDaS: Representative Sampling from Real-world Hypergraphs

    Minyoung Choe, Jaemin Yoo, Geon Lee, Woonsung Baek, U Kang, Kijung Shin

  18. CGC: Contrastive Graph Clustering for Community Detection and Tracking

    Namyong Park, Ryan A. Rossi, Eunyee Koh, Iftikhar Ahamath Burhanuddin, Sungchul Kim, Fan Du, Nesreen K. Ahmed, Christos Faloutsos

  19. Graph Neural Networks Beyond Compromise Between Attribute and Topology

    Liang Yang, Wenmiao Zhou, Weihang Peng, Bingxin Niu, Junhua Gu, Chuan Wang, Xiaochun Cao, Dongxiao He

  20. Graph Sanitation with Application to Node Classification

    Zhe Xu, Boxin Du, Hanghang Tong

  21. TREND: TempoRal Event and Node Dynamics for Graph Representation Learning

    Zhihao Wen, Yuan Fang

  22. Resource-Efficient Training for Large Graph Convolutional Networks with Label-Centric Cumulative Sampling

    Mingkai Lin, Wenzhong Li, Ding Li, Yizhou Chen, Sanglu Lu

  23. Graph Communal Contrastive Learning

    Bolian Li, Baoyu Jing, Hanghang Tong

  24. Geometric Graph Representation Learning via Maximizing Rate Reduction

    Xiaotian Han, Zhimeng Jiang, Ninghao Liu, Qingquan Song, Jundong Li, Xia Hu

  25. Dual Space Graph Contrastive Learning

    Haoran Yang, Hongxu Chen, Shirui Pan, Lin Li, Philip S. Yu, Guandong Xu

  26. Confidence May Cheat: Self-Training on Graph Neural Networks under Distribution Shift

    Hongrui Liu, Binbin Hu, Xiao Wang, Chuan Shi, Zhiqiang Zhang, Jun Zhou

  27. EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks

    Yushun Dong, Ninghao Liu, Brian Jalaian, Jundong Li

  28. Meta-Weight Graph Neural Network: Push the Limits Beyond Global Homophily

    Xiaojun Ma, Qin Chen, Yuanyi Ren, Guojie Song, Liang Wang

  29. Model-Agnostic Augmentation for Accurate Graph Classification

    Jaemin Yoo, Sooyeon Shim, U Kang

  30. Multimodal Continual Graph Learning with Neural Architecture Search

    Jie Cai, Xin Wang, Chaoyu Guan, Yateng Tang, Jin Xu, Bin Zhong, Wenwu Zhu

  31. AUC-oriented Graph Neural Network for Fraud Detection

    Mengda Huang, Yang Liu, Xiang Ao, Kuan Li, Jianfeng Chi, Jinghua Feng, Hao Yang, Qing He

  32. Unsupervised Graph Poisoning Attack via Contrastive Loss Back-propagation

    Sixiao Zhang, Hongxu Chen, Xiangguo Sun, Yicong Li, Guandong Xu

  33. Graph-adaptive Rectified Linear Unit for Graph Neural Networks

    Yifei Zhang, Hao Zhu, Ziqiao Meng, Piotr Koniusz, Irwin King

  34. Robust Self-Supervised Structural Graph Neural Network for Social Network Prediction

    Yanfu Zhang, Hongchang Gao, Jian Pei, Heng Huang

  35. Adversarial Graph Contrastive Learning with Information Regularization

    Shengyu Feng, Baoyu Jing, Yada Zhu, Hanghang Tong

  36. Designing the Topology of Graph Neural Networks: A Novel Feature Fusion Perspective

    Lanning Wei, Huan Zhao, Zhiqiang He

  37. Towards Unsupervised Deep Graph Structure Learning

    Yixin Liu, Yu Zheng, Daokun Zhang, Hongxu Chen, Hao Peng, Shirui Pan

  38. Polarized Graph Neural Networks

    Zheng Fang, Lingjun Xu, Guojie Song, Qingqing Long, Yingxue Zhang

  39. Unbiased Graph Embedding with Biased Graph Observations

    Nan Wang, Lu Lin, Jundong Li, Hongning Wang

  40. Prohibited Item Detection via Risk Graph Structure Learning

    Yugang Ji, Guanyi Chu, Xiao Wang, Chuan Shi, Jianan Zhao, Junping Du

  41. Inflation Improves Graph Neural Networks

    Dongxiao He, Rui Guo, Xiaobao Wang, Di Jin, Yuxiao Huang, Wenjun Wang

  42. Generating Simple Directed Social Network Graphs for Information Spreading

    Christoph Schweimer, Christine Gfrerer, Florian Lugstein, David Pape, Jan A. Velimsky, Robert Elsässer, Bernhard C. Geiger

  43. On Size-Oriented Long-Tailed Graph Classification of Graph Neural Networks

    Zemin Liu, Qiheng Mao, Chenghao Liu, Yuan Fang, Jianling Sun

  44. Curvature Graph Generative Adversarial Networks

    Jianxin Li, Xingcheng Fu, Qingyun Sun, Cheng Ji, Jiajun Tan, Jia Wu, Hao Peng

  45. Augmentations in Graph Contrastive Learning: Current Methodological Flaws & Towards Better Practices

    Puja Trivedi, Ekdeep Singh Lubana, Yujun Yan, Yaoqing Yang, Danai Koutra

  46. GBK-GNN: Gated Bi-Kernel Graph Neural Networks for Modeling Both Homophily and Heterophily

    Lun Du, Xiaozhou Shi, Qiang Fu, Xiaojun Ma, Hengyu Liu, Shi Han, Dongmei Zhang

  47. Compact Graph Structure Learning via Mutual Information Compression

    Nian Liu, Xiao Wang, Lingfei Wu, Yu Chen, Xiaojie Guo, Chuan Shi

  48. ClusterSCL: Cluster-Aware Supervised Contrastive Learning on Graphs

    Yanling Wang, Jing Zhang, Haoyang Li, Yuxiao Dong, Hongzhi Yin, Cuiping Li, Hong Chen

  49. Graph Neural Network for Higher-Order Dependency Networks

    Di Jin, Yingli Gong, Zhiqiang Wang, Zhizhi Yu, Dongxiao He, Yuxiao Huang, Wenjun Wang

  50. PaSca: A Graph Neural Architecture Search System under the Scalable Paradigm

    Wentao Zhang, Yu Shen, Zheyu Lin, Yang Li, Xiaosen Li, Wen Ouyang, Yangyu Tao, Zhi Yang, Bin Cui

  51. Element-guided Temporal Graph Representation Learning for Temporal Sets Prediction

    Le Yu, Guanghui Wu, Leilei Sun, Bowen Du, Weifeng Lv

  52. Hypercomplex Graph Collaborative Filtering

    Anchen Li, Bo Yang, Huan Huo, Farookh Khadeer Hussain

  53. Graph Neural Transport Networks with Non-local Attentions for Recommender Systems

    Huiyuan Chen, Chin-Chia Michael Yeh, Fei Wang, Hao Yang

  54. Multi-level Recommendation Reasoning over Knowledge Graphs with Reinforcement Learning

    Xiting Wang, Kunpeng Liu, Dongjie Wang, Le Wu, Yanjie Fu, Xing Xie

  55. GSL4Rec: Session-based Recommendations with Collective Graph Structure Learning and Next Interaction Prediction

    Chunyu Wei, Bing Bai, Kun Bai, Fei Wang

  56. Graph-based Extractive Explainer for Recommendations

    Peng Wang, Renqin Cai, Hongning Wang

  57. Improving Graph Collaborative Filtering with Neighborhood-enriched Contrastive Learning

    Zihan Lin, Changxin Tian, Yupeng Hou, Wayne Xin Zhao

  58. Evidence-aware Fake News Detection with Graph Neural Networks

    Weizhi Xu, Junfei Wu, Qiang Liu, Shu Wu, Liang Wang

  59. Rumor Detection on Social Media with Graph Adversarial Contrastive Learning

    Tiening Sun, Zhong Qian, Sujun Dong, Peifeng Li, Qiaoming Zhu

  60. VisGNN: Personalized Visualization Recommendationvia Graph Neural Networks

    Fayokemi Ojo, Ryan A. Rossi, Jane Hoffswell, Shunan Guo, Fan Du, Sungchul Kim, Chang Xiao, Eunyee Koh

  61. Revisiting Graph based Social Recommendation: A Distillation Enhanced Social Graph Network

    Ye Tao, Ying Li, Su Zhang, Zhirong Hou, Zhonghai Wu

  62. DiriE: Knowledge Graph Embedding with Dirichlet Distribution

    Feiyang Wang, Zhongbao Zhang, Li Sun, Junda Ye, Yang Yan

  63. STAM: A Spatiotemporal Aggregation Method for Graph Neural Network-based Recommendation

    Zhen Yang, Ming Ding, Bin Xu, Hongxia Yang, Jie Tang

  64. GRAND+: Scalable Graph Random Neural Networks

    Wenzheng Feng, Yuxiao Dong, Tinglin Huang, Ziqi Yin, Xu Cheng, Evgeny Kharlamov, Jie Tang

  65. Large-scale Personalized Video Game Recommendation via Social-aware Contextualized Graph Neural Network

    Liangwei Yang, Zhiwei Liu, Yu Wang, Chen Wang, Ziwei Fan, Philip S. Yu

  66. Learning Privacy-Preserving Graph Convolutional Network with Partially Observed Sensitive Attributes

    Hui Hu, Lu Cheng, Jayden Parker Vap, Mike Borowczak

  1. BinarizedAttack: Structural Poisoning Attacks to Graph-based Anomaly Detection

    Yulin Zhu, Yuni Lai, Kaifa Zhao, Xiapu Luo, Mingquan Yuan, Jian Ren, Kai Zhou

  2. Accurate and Scalable Graph Neural Networks for Billion-Scale Graphs

    Juxiang Zeng, Pinghui Wang, Lin Lan, Junzhou Zhao, Feiyang Sun, Jing Tao, Junlan Feng, Min Hu, Xiaohong Guan

  3. Attentive Knowledge-aware Graph Convolutional Networks with Collaborative Guidance for Personalized Recommendation

    Yankai Chen, Yaming Yang, Yujing Wang, Jing Bai, Xiangchen Song, Irwin King

  4. Academic Expert Finding via $(k, \mathcal{P})$-Core based Embedding over Heterogeneous Graphs

    Xiaoliang Xu, Jun Liu, Yuxiang Wang, Xiangyu Ke

  5. AutoHEnsGNN: Winning Solution to AutoGraph Challenge for KDD Cup 2020

    Jin Xu, Mingjian Chen, Jianqiang Huang, Xingyuan Tang, Ke Hu, Jian Li, Jia Cheng, Jun Lei

  6. SLUGGER: Lossless Hierarchical Summarization of Massive Graphs

    Kyuhan Lee, Jihoon Ko, Kijung Shin

  7. $O^{2}$-SiteRec: Store Site Recommendation under the O2O Model via Multi-graph Attention Networks

    Hua Yan, Shuai Wang, Yu Yang, Baoshen Guo, Tian He, Desheng Zhang

  8. A Data-Driven Spatial-Temporal Graph Neural Network for Docked Bike Prediction

    Guanyao Li, Xiaofeng Wang, Gunarto Sindoro Njoo, Shuhan Zhong, S.-H. Gary Chan, Chih-Chieh Hung, Wen-Chih Peng

  9. Black-box Adversarial Attack and Defense on Graph Neural Networks

    Haoyang Li, Shimin Di, Zijian Li, Lei Chen, Jiannong Cao

  10. MAD-SGCN: Multivariate Anomaly Detection with Self-learning Graph Convolutional Networks

    Panpan Qi, Dan Li, See-Kiong Ng

  11. On Compressing Temporal Graphs

    Panagiotis Liakos, Katia Papakonstantinopoulou, Theodore Stefou, Alex Delis

  12. Dynamic Hypergraph Convolutional Network

    Nan Yin, Fuli Feng, Zhigang Luo, Xiang Zhang, Wenjie Wang, Xiao Luo, Chong Chen, Xian-Sheng Hua

  13. PSP: Progressive Space Pruning for Efficient Graph Neural Architecture Search

    Guanghui Zhu, Wenjie Wang, Zhuoer Xu, Feng Cheng, Mengchuan Qiu, Chunfeng Yuan, Yihua Huang

  14. HET-KG: Communication-Efficient Knowledge Graph Embedding Training via Hotness-Aware Cache

    Sicong Dong, Xupeng Miao, Pengkai Liu, Xin Wang, Bin Cui, Jianxin Li

  15. Spatial-Temporal Hypergraph Self-Supervised Learning for Crime Prediction

    Zhonghang Li, Chao Huang, Lianghao Xia, Yong Xu, Jian Pei

  16. BA-GNN: On Learning Bias-Aware Graph Neural Network

    Zhengyu Chen, Teng Xiao, Kun Kuang

  17. VICS-GNN: A Visual Interactive System for Community Search via Graph Neural Network

    Jiazun Chen, Jun Gao

  18. Tower Bridge Net (TB-Net): Bidirectional Knowledge Graph Aware Embedding Propagation for Explainable Recommender Systems

    Shendi Wang, Haoyang Li, Caleb Chen Cao, Xiao-Hui Li, Ng Ngai Fai, Jianxin Liu, Xun Xue, Hu Song, Jinyu Li, Guangye Gu, Lei Chen

  19. Gaia: Graph Neural Network with Temporal Shift aware Attention for Gross Merchandise Value Forecast in E-commerce

    Borui Ye, Shuo Yang, Binbin Hu, Zhiqiang Zhang, Youqiang He, Kai Huang, Jun Zhou, Yanming Fang

  1. Entity Resolution with Hierarchical Graph Attention Networks

    Dezhong Yao, Yuhong Gu, Gao Cong, Hai Jin, Xinqiao Lv

  2. Compact Walks: Taming Knowledge-Graph Embeddings with Domain- and Task-Specific Pathways

    Pei-Yu Hou, Daniel Robert Korn, Cleber C. Melo-Filho, David R. Wright, Alexander Tropsha, Rada Chirkova

  3. Explaining Link Prediction Systems based on Knowledge Graph Embeddings

    Andrea Rossi, Donatella Firmani, Paolo Merialdo, Tommaso Teofili

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Advances on machine learning of graphs, covering the reading list of recent top academic conferences.

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