diff --git a/github_links.txt b/github_links.txt index 429947d..ecfac06 100644 --- a/github_links.txt +++ b/github_links.txt @@ -1,583 +1,549 @@ -https://github.com/youngfish42/Awesome-FL/issues -https://github.com/omarfoq/FedEM -https://github.com/haoyangliASTAPLE/3DFed -https://github.com/gaoliang13/FedDC -https://github.com/TsingZ0/DBE -https://github.com/IBM/probabilistic-federated-neural-matching -https://github.com/alibaba/FederatedScope/tree/FSreal -https://github.com/dual-grp/fedu_fmtl -https://github.com/yutong-dai/fednh -https://github.com/BUAA-CST/iLRG -https://github.com/carbonati/fl-zoo -https://github.com/FuChong-cyber/label-inference-attacks -https://github.com/gingsmith/fmtl -https://github.com/scaleoutsystems/fedn -https://github.com/ignavierng/notears-admm -https://github.com/ellenxtan/ifedtree -https://github.com/royson/fedl2p/ -https://github.com/appy1608/EMNLP2023-Multimodal-Complaint-Detection -https://github.com/lokinko/Federated-Learning -https://github.com/aioz-ai/MultigraphFL -https://github.com/omarfoq/communication-in-cross-silo-fl -https://github.com/hmgxr128/MIFA_code/ -https://github.com/KarhouTam/FedRecon -https://github.com/LipingYi/FedGH -https://github.com/ZJU-DIVER/ShapleyFL-Robust-Federated-Learning-Based-on-Shapley-Value -https://github.com/jeremy313/FL-WBC -https://github.com/HewlettPackard/swarm-learning/blob/master/docs/videos.md -https://github.com/hyhmia/DisTrans -https://github.com/pengyang7881187/fedrl -https://github.com/QuanlingZhao/FedHD -https://github.com/lowya/private-federated-learning-without-a-trusted-server -https://github.com/zshuai8/FedGMM_ICML2023 -https://github.com/IBM/federated-learning-lib/blob/main/docs/papers.md -https://github.com/lzcemma/RACE_Distance -https://github.com/secretflow/secretflow -https://github.com/harliwu/fedagrac -https://github.com/ycruan/FedSoft -https://github.com/SymbioticLab/Oort -https://github.com/a514514772/ProgFed -https://github.com/Soptq/iccv23-3sfc 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+https://github.com/ElvisShaoYumeng/BLADE-FL https://github.com/Emory-AIMS/PFA -https://github.com/basiralab/Fed-CBT -https://github.com/llpilla/energy-optimal-federated-learning -https://github.com/jedmills/fedgbo -https://github.com/MediaBrain-SJTU/FedDG-GA -https://github.com/shenzebang/CENTAUR-Privacy-Federated-Representation-Learning -https://github.com/hasakiXie123/FedCMR -https://github.com/alibaba-edu/mpc4j/tree/main/mpc4j-sml-opboost -https://github.com/farzanfarnia/RobustFL -https://github.com/dawenzi098/SFL-Structural-Federated-Learning -https://github.com/SymbioticLab/FedScale -https://github.com/FederatedAI/research/tree/main/publications/FedCG -https://github.com/ShahryarBQ/EF_HC -https://github.com/FederatedAI/KubeFATE -https://github.com/dunchen/AsyncDrop__Release -https://github.com/litian96/FedProx -https://github.com/sabersalehk/MRE_C -https://github.com/sfu-db/FedRain-and-Frog -https://github.com/czhang024/CI-Net -https://github.com/tfzhou/fedfa -https://github.com/MoonkeyBoy/Federated-Unlearning-via-Class-Discriminative-Pruning -https://github.com/bl166/wirelessfl-pdgnet -https://github.com/optimization-ai/icml2023_fedxl -https://github.com/eric-ai-lab/FedVLN -https://github.com/VITA-Group/MaT-FL -https://github.com/git-disl/STDLens -https://github.com/baowenxuan/ATP -https://github.com/facebookresearch/dp_compression -https://github.com/wnn2000/fednoro -https://github.com/KaiyuanZh/FLIP -https://github.com/baowenxuan/fedcollab +https://github.com/FETS-AI/Front-End https://github.com/FL-HAR/Graph-Federated-Learning-for-CIoT-Devices.git -https://github.com/wyjeong/FedMatch -https://github.com/LTTM/FedSpace/blob/main/media/slides.pdf -https://github.com/NVlabs/FedFomo -https://github.com/nds2022/SGBoost -https://github.com/SMILELab-FL/FedVocab -https://github.com/FedML-AI/FedML -https://github.com/tsingz0/fedcp -https://github.com/bdemo/pfedbred_public -https://github.com/ShenGroup/FMAB -https://github.com/fio1982/FlexiFed -https://github.com/zexilee/icml-2023-fedlaw -https://github.com/alshedivat/fedpa -https://github.com/junyizhu-ai/confidence_aware_pfl -https://github.com/Soptq/Overlap-FedAvg -https://github.com/baichuanzheng1/fedgat -https://github.com/lebyni/PFA -https://github.com/Samuel-Maddock/federated-boosted-dp-trees -https://github.com/XinyiYS/Gradient-Driven-Rewards-to-Guarantee-Fairness-in-Collaborative-Machine-Learning -https://github.com/illidanlab/FADE -https://github.com/AllenBeau/pFedBayes +https://github.com/FRM-Sec/FRM +https://github.com/FangXiuwen/AugHFL https://github.com/FangXiuwen/Robust_FL -https://github.com/SAP-samples/machine-learning-diff-private-federated-learning -https://github.com/YuchenLiu-a/byzantine-gas +https://github.com/FedML-AI/FedCV +https://github.com/FedML-AI/FedGraphNN +https://github.com/FedML-AI/FedML +https://github.com/FedML-AI/FedNLP +https://github.com/FedML-AI/SpreadGNN +https://github.com/FederalLab/OpenFed +https://github.com/FederalLab/OpenFed/ +https://github.com/FederatedAI/FATE +https://github.com/FederatedAI/FATE-Serving +https://github.com/FederatedAI/FedVision +https://github.com/FederatedAI/KubeFATE +https://github.com/FederatedAI/research +https://github.com/FengHZ/KD3A +https://github.com/FuChong-cyber/label-inference-attacks +https://github.com/FumiyukiKato/FL-TEE +https://github.com/GalaxyLearning/GFL https://github.com/GanyuWang/VFL-CZOFO -https://github.com/ahmedcs/refl -https://github.com/jhoon-oh/FedBABU -https://github.com/Accenture/Labs-Federated-Learning/tree/asynchronous_FL +https://github.com/GwenLegate/GuidingLastLayerFLPretrain +https://github.com/HKUST-KnowComp/FKGE +https://github.com/HUST-EIC-AI-LAB/UCADI +https://github.com/HaifengXia/PSE +https://github.com/Hanzhouu/FedBFPT +https://github.com/HarlinLee/multitask-fusion +https://github.com/HewlettPackard/swarm-learning +https://github.com/HikariX/MP-FedXGB +https://github.com/HuskyW/FFPA +https://github.com/Hypervoyager/PFL 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+https://github.com/IntelligentNetworkingLAB/Graph-Neural-Network-based-Federated-Learning-for-Heterogenous-Device-Network +https://github.com/J1nqianChen/FedKA +https://github.com/JYWa/FedNova +https://github.com/JackqqWang/pfedHR +https://github.com/JedMills/Faster-FL +https://github.com/JedMills/MTFL-For-Personalised-DNNs +https://github.com/JiahuaDong/FISS +https://github.com/JianXu95/FedPAC +https://github.com/JinheonBaek/FED-PUB +https://github.com/JonasGeiping/breaching +https://github.com/JonasGeiping/invertinggradients +https://github.com/KAI-YUE/ntk-fed +https://github.com/KAI-YUE/rog +https://github.com/KaiyuanZh/FLIP +https://github.com/KarhouTam/FedRecon +https://github.com/KarhouTam/Per-FedAvg +https://github.com/Kira0096/PBPFL +https://github.com/Koukyosyumei/AIJack +https://github.com/Koukyosyumei/NAIST-FedML-Experiments +https://github.com/Kthyeon/ssfod +https://github.com/LTTM/FedSpace +https://github.com/LabeliaLabs/distributed-learning-contributivity +https://github.com/LatticeX-Foundation/Rosetta +https://github.com/Liangqiong/ViT-FL-main +https://github.com/LightSecAgg/MLSys2022_anonymous +https://github.com/LipingYi/FedGH +https://github.com/LipingYi/QSFL +https://github.com/LiruichenSpace/FedFusion +https://github.com/MLOPTPSU/FedTorch +https://github.com/MSU-MLSys-Lab/FedRolex https://github.com/MTC-ETH/Federated-Learning-source -https://github.com/YMJS-Irfan/DP-FedSAM -https://github.com/harliwu/fedamd -https://github.com/WenkeHuang/RethinkFL -https://github.com/cuhksz-nlp/ASA-TM -https://github.com/SkellamMixtureMechanism/SMM -https://github.com/kaiyuanmifen/FederatedNLP -https://github.com/liecn/PyramidFL -https://github.com/clreda/near-optimal-federated -https://github.com/litian96/fair_flearn -https://github.com/Xtra-Computing/FedSim -https://github.com/hgh0545/graph-fraudster -https://github.com/hongyouc/fedbe -https://github.com/ycao5602/KAFAL -https://github.com/wrh14/learning_to_invert 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+https://github.com/Ruiquan5514/Federated-Linear-Contextual-Bandits +https://github.com/SAP-samples/machine-learning-diff-private-federated-learning +https://github.com/SEED-VT/FedDebug +https://github.com/SMILELab-FL/FedLab https://github.com/SMILELab-FL/FedLab-benchmarks -https://github.com/ccchengff/FDL/tree/main/playground/celu_vfl -https://github.com/cuis15/learning-to-collaborate -https://github.com/codymlewis/viceroy +https://github.com/SMILELab-FL/FedLegal +https://github.com/SMILELab-FL/FedVocab +https://github.com/Samuel-Maddock/federated-boosted-dp-trees +https://github.com/SamuelHorvath/VR_Byzantine +https://github.com/SaraBabakN/MFCL-NeurIPS23 +https://github.com/ShahryarBQ/EF_HC +https://github.com/ShenGroup/FMAB +https://github.com/ShenGroup/PF_MAB https://github.com/ShenglongZhou/FedADMM -https://github.com/HewlettPackard/swarm-learning +https://github.com/SkellamMixtureMechanism/SMM +https://github.com/SongjieXie/Fed-SC +https://github.com/SonyAI/MocoSFL +https://github.com/Soptq/Overlap-FedAvg +https://github.com/Soptq/iccv23-3sfc +https://github.com/South-hw/FedPara_ICLR22 +https://github.com/Spinozaaa/Federated-Long-tailed-Learning https://github.com/Strange369/TypedDAG_on_HeteroMP -https://github.com/Oxfordblue7/GCFL -https://github.com/AI-secure/DBA -https://github.com/dem123456789/HeteroFL-Computation-and-Communication-Efficient-Federated-Learning-for-Heterogeneous-Clients -https://github.com/vrt1shjwlkr/NDSS21-Model-Poisoning -https://github.com/dongzizhu/FedDA -https://github.com/FederatedAI/FATE-Serving -https://github.com/insujeon/MetaVD -https://github.com/lgcollins/FedRep -https://github.com/xj231/featureinference-vfl -https://github.com/minglllli/CBAFed -https://github.com/zkhku/fedsage -https://github.com/ybdai7/chameleon-durable-backdoor -https://github.com/akhilmathurs/orchestra -https://github.com/totilas/padadmm -https://github.com/daizhongxiang/Differentially-Private-Federated-Bayesian-Optimization -https://github.com/illidanlab/FOSTER -https://github.com/KarhouTam/Per-FedAvg -https://github.com/FederalLab/OpenFed/ -https://github.com/rand2ai/fedboost +https://github.com/Substra/substra +https://github.com/Sungwon-Han/FEDCPA +https://github.com/SymbioticLab/FedScale +https://github.com/SymbioticLab/Oort +https://github.com/TCtower/GlueFL +https://github.com/TL-System/plato +https://github.com/TL-System/plato/ +https://github.com/TalwalkarLab/leaf +https://github.com/Thinklab-SJTU/GAMF +https://github.com/TinfoilHat0/Defending-Against-Backdoors-with-Robust-Learning-Rate +https://github.com/TsingZ0/DBE +https://github.com/TsingZ0/GPFL +https://github.com/TsingZ0/PFL-Non-IID +https://github.com/TsingZ0/PFLlib +https://github.com/VITA-Group/MaT-FL +https://github.com/WeiNingChen/pbm +https://github.com/WenkeHuang/FSMAFL +https://github.com/WenkeHuang/RethinkFL https://github.com/WwZzz/easyFL -https://github.com/zhuangdizhu/FedGen -https://github.com/taokz/FedR -https://github.com/orionw/multilingual-federated-learning -https://github.com/gdisag/gradient_disaggregation -https://github.com/jcwang123/fedlc -https://github.com/FedML-AI/SpreadGNN -https://github.com/DianboWork/FedDS -https://github.com/zhangcx19/ijcai-23-pfedrec -https://github.com/alibaba/FederatedScope -https://github.com/hit-mdc/FedTSC-FedST -https://github.com/QibingLee/OpenHealth -https://github.com/AI-secure/CRFL -https://github.com/FedML-AI/FedGraphNN -https://github.com/Liangqiong/ViT-FL-main -https://github.com/ebagdasa/backdoors101 -https://github.com/CGCL-codes/pFedSD -https://github.com/wingter562/SAFA -https://github.com/ml-unito/federation_boosting -https://github.com/iwang05/FLuID -https://github.com/ljb121002/fednar -https://github.com/zhaohaoru/federated-clustering-of-bandits -https://github.com/tsingz0/fedala +https://github.com/XDUJiaweiChen/Dap-FL +https://github.com/XinyiYS/Gradient-Driven-Rewards-to-Guarantee-Fairness-in-Collaborative-Machine-Learning +https://github.com/Xtra-Computing/FedSim +https://github.com/Xtra-Computing/FedTree https://github.com/Xtra-Computing/NIID-Bench -https://github.com/ElvisShaoYumeng/BLADE-FL -https://github.com/deu30303/feddefender -https://github.com/ghafeleb/Private-NonConvex-Federated-Learning-Without-a-Trusted-Server -https://github.com/iQua/flsim -https://github.com/jinkyu032/FedMLB -https://github.com/RamiHaf/Explainable-Federated-Learning-via-Random-Forests -https://github.com/wenkehuang/fccl -https://github.com/PKU-Chengxu/FLASH -https://github.com/debcaldarola/fedsam -https://github.com/maxencenoble/Differential-Privacy-for-Heterogeneous-Federated-Learning -https://github.com/LightSecAgg/MLSys2022_anonymous -https://github.com/jeremy313/Soteria -https://github.com/QinbinLi/FedKT -https://github.com/sunjunaimer/TPAMI-LAQ -https://github.com/xkLi-Allen/FedGTA +https://github.com/Xtra-Computing/PrivML +https://github.com/Xtra-Computing/SimFL +https://github.com/XunKaiLi/Awesome-GNN-Research +https://github.com/YMJS-Irfan/DP-FedSAM +https://github.com/YamingGuo98/FedIIR +https://github.com/YangLiangwei/FeSoG https://github.com/YonghaiGong/FedADMM +https://github.com/YuchenLiu-a/byzantine-gas +https://github.com/Yujun-Shi/FedCLS +https://github.com/ZFancy/SFAT +https://github.com/ZJU-DIVER/ShapleyFL-Robust-Federated-Learning-Based-on-Shapley-Value +https://github.com/ZackZikaiXiao/FedGraB +https://github.com/Zoesgithub/FedReg +https://github.com/a514514772/ProgFed +https://github.com/abhimanyudubey/private_federated_linear_bandits +https://github.com/adap/flower +https://github.com/aelgabli/FedNew +https://github.com/ahmedcs/refl +https://github.com/aioz-ai/MultigraphFL +https://github.com/akhilmathurs/orchestra +https://github.com/albietz/ppsgd +https://github.com/alibaba/FederatedScope +https://github.com/alshedivat/fedpa +https://github.com/amitport/DRIVE-One-bit-Distributed-Mean-Estimation https://github.com/amitport/EDEN-Distributed-Mean-Estimation -https://github.com/cuis15/FCFL -https://github.com/exquisite1210/PT-FUCH_P -https://github.com/dual-grp/DONE +https://github.com/andylamp/federated_pca +https://github.com/andytu28/fps_pre-training +https://github.com/anishacharya/DeLiCoCo +https://github.com/appy1608/EMNLP2023-Multimodal-Complaint-Detection +https://github.com/arodio/ca-fed +https://github.com/baichuanzheng1/fedgat +https://github.com/balanced-fl/Addressing-Class-Imbalance-FL +https://github.com/baowenxuan/ATP +https://github.com/baowenxuan/fedcollab +https://github.com/basiralab/Fed-CBT +https://github.com/basiralab/reproducibleFedGNN +https://github.com/bdemo/pfedbred_public +https://github.com/benggggggggg/fedgame +https://github.com/bibikar/feddst +https://github.com/bingzhaozhu/xtab +https://github.com/bl166/wirelessfl-pdgnet +https://github.com/bokun-wang/moml +https://github.com/boxinz17/data-market-via-adaptive-sampling +https://github.com/bytedance/fedlearner +https://github.com/cap-ntu/FedReID +https://github.com/carbonati/fl-zoo https://github.com/cfh19980612/FedGraph -https://github.com/mysteryresearcher/dasha -https://github.com/unc-optimization/FedDR -https://github.com/CharlieMat/EdgeCDR +https://github.com/chandra2thapa/SplitFed-When-Federated-Learning-Meets-Split-Learning https://github.com/chaoyanghe/Awesome-Federated-Learning -https://github.com/jd-9n/9nfl -https://github.com/MediaBrain-SJTU/FedGELA +https://github.com/chaoyitud/LeadFL +https://github.com/chuanting/fedda +https://github.com/chunmeifeng/FedPR +https://github.com/chunmeifeng/fedins +https://github.com/cisco-open/flame +https://github.com/citychan/federated-dpms +https://github.com/clreda/near-optimal-federated +https://github.com/clu5/federated-conformal +https://github.com/codymlewis/viceroy https://github.com/conditionWang/FCIL -https://github.com/AI-secure/FedGame -https://github.com/pierreHmbt/FedCP-QQ -https://github.com/zhanghangtao/poisoning-attack-on-fl -https://github.com/yuetan031/fedstar -https://github.com/eniac/flamingo -https://github.com/South-hw/FedPara_ICLR22 -https://github.com/ielab/2022-SIGIR-noniid-foltr -https://github.com/rdz98/fedrecattack +https://github.com/corentingiraud/federated-learning-secure-aggregation +https://github.com/cugzj/KT-pFL +https://github.com/cuhksz-nlp/ASA-TM +https://github.com/cuhksz-nlp/GCASeg +https://github.com/cuis15/FCFL +https://github.com/cuis15/learning-to-collaborate https://github.com/culiver/SPACE -https://github.com/jiayunz/fedalign -https://github.com/siquanhuang/Multi-metrics_against_backdoors_in_FL -https://github.com/teijyogen/secsv -https://github.com/chuanting/fedda -https://github.com/international-explore/awesome-privacy-chinese -https://github.com/DCALab-UNIPV/Turning-Privacy-preserving-Mechanisms-against-Federated-Learning -https://github.com/jma78/FedGTF-EF -https://github.com/hanguo97/expectation-propagation -https://github.com/FederalLab/OpenFed -https://github.com/Ruiquan5514/Federated-Linear-Contextual-Bandits -https://github.com/owkin/FLamby -https://github.com/Hanzhouu/FedBFPT -https://github.com/FETS-AI/Front-End -https://github.com/Kthyeon/ssfod -https://github.com/yzhao062/anomaly-detection-resources -https://github.com/OpenMined/SyferText -https://github.com/taoqi98/PrivateKT -https://github.com/shahakash28/simc -https://github.com/Princeton-SysML/FILM -https://github.com/guskarls/dfl-pens -https://github.com/shangxinyi/CReFF-FL -https://github.com/mkhodak/fedex -https://github.com/hfzhang31/A3FL -https://github.com/xmed-lab/rscfed -https://github.com/JonasGeiping/invertinggradients -https://github.com/inspire-group/ModelPoisoning -https://github.com/junyizhu-ai/surrogate_model_extension -https://github.com/zexilee/iccv-2023-fedetf -https://github.com/AfoninAndrei/ICLR2022 -https://github.com/guopengf/FL-MRCM -https://github.com/arodio/ca-fed -https://github.com/FederatedAI/FATE/tree/master/python/federatedml/ensemble/secureboost -https://github.com/Koukyosyumei/NAIST-FedML-Experiments -https://github.com/shams-sam/FedOptim -https://github.com/FederatedAI/research -https://github.com/amitport/DRIVE-One-bit-Distributed-Mean-Estimation -https://github.com/primihub/primihub -https://github.com/med-air/HarmoFL -https://github.com/OpenMined/PyVertical -https://github.com/youngfish42/FL-paper-update-tracker -https://github.com/MediaBrain-SJTU/FedDisco -https://github.com/ShenGroup/PF_MAB -https://github.com/MarcioPorto/federated-phenotyping -https://github.com/Zoesgithub/FedReg -https://github.com/nusdbsystem/falcon -https://github.com/FedML-AI/FedML/tree/master/fedml_experiments/distributed/fedgkt +https://github.com/cyberthreat-datasets/ctdd-2021-os-syslogs +https://github.com/cynricfu/FedHGN +https://github.com/cynricfu/fedhgn https://github.com/cyrilli/Async-LinUCB -https://github.com/hongyouc/Fed-RoD -https://github.com/TL-System/plato/ -https://github.com/anishacharya/DeLiCoCo -https://github.com/med-air/FedBN -https://github.com/FederatedAI/FATE -https://github.com/Raymw/Federated-XGBoost -https://github.com/Oxfordblue7/FedLIT -https://github.com/morningD/GrouProx -https://github.com/wanglun1996/secure-robust-federated-learning -https://github.com/kpdonahue/model_sharing_games -https://github.com/XDUJiaweiChen/Dap-FL -https://github.com/git-disl/scale-fl +https://github.com/cyyever/distributed_learning_simulator +https://github.com/czhang024/CI-Net +https://github.com/daiqing98/FedCIL +https://github.com/daizhongxiang/Differentially-Private-Federated-Bayesian-Optimization +https://github.com/daizhongxiang/Federated_Bayesian_Optimization +https://github.com/dawenzi098/SFL-Structural-Federated-Learning +https://github.com/debcaldarola/fedsam https://github.com/deep1401/fedmoji -https://github.com/google-research/federated/tree/f4e26c1b9b47ac320e520a8b9943ea2c5324b8c2/large_cohort -https://github.com/morningD/FlexCFL +https://github.com/dem123456789/HeteroFL-Computation-and-Communication-Efficient-Federated-Learning-for-Heterogeneous-Clients +https://github.com/deu30303/feddefender +https://github.com/divyansh03/fedexp +https://github.com/dongzizhu/FedDA +https://github.com/dual-grp/DONE +https://github.com/dual-grp/fedu_fmtl +https://github.com/dunchen/AsyncDrop__Release +https://github.com/ebagdasa/backdoor_federated_learning +https://github.com/ebagdasa/backdoors101 +https://github.com/ellenxtan/ifedtree +https://github.com/eniac/flamingo +https://github.com/enosair/federated-fdp +https://github.com/eric-ai-lab/FedVLN https://github.com/eth-sri/bayes-framework-leakage -https://github.com/wuch15/FedAttack -https://github.com/FumiyukiKato/FL-TEE -https://github.com/yh-yao/FedGCN -https://github.com/kiddyboots216/CommEfficient -https://github.com/abhimanyudubey/private_federated_linear_bandits -https://github.com/JonasGeiping/breaching -https://github.com/SMILELab-FL/FedLab -https://github.com/HaifengXia/PSE -https://github.com/liuquande/FedDG-ELCFS -https://github.com/Xtra-Computing/PrivML -https://github.com/AI-secure/FLBenchmark-toolkit -https://github.com/rong-dai/DisPFL -https://github.com/garyzhang99/DM-PFL https://github.com/eth-sri/tableak -https://github.com/lancopku/fedmnmt -https://github.com/haozzh/FedCR -https://github.com/GOGODD/FL-EDGE-COMPUTING/releases/tag/federated_learning -https://github.com/MSU-MLSys-Lab/FedRolex -https://github.com/zhuohangli/GGL -https://github.com/SongjieXie/Fed-SC -https://github.com/Hypervoyager/PFL -https://github.com/GwenLegate/GuidingLastLayerFLPretrain -https://github.com/YangLiangwei/FeSoG -https://github.com/intel/openfl -https://github.com/CodePothunter/fednp -https://github.com/AnselCmy/FedE -https://github.com/rasmus-pagh/private-countsketch -https://github.com/LTTM/FedSpace -https://github.com/basiralab/reproducibleFedGNN -https://github.com/JackqqWang/pfedHR -https://github.com/XunKaiLi/Awesome-GNN-Research -https://github.com/zfan20/PFGNNPlus -https://github.com/yuetan031/fedproto -https://github.com/Substra/substra -https://github.com/aelgabli/FedNew -https://github.com/bingzhaozhu/xtab -https://github.com/PaddlePaddle/PaddleFL -https://github.com/YamingGuo98/FedIIR -https://github.com/yasar-rehman/fedvssl -https://github.com/mindspore-ai/mindspore/tree/master/docs/api/api_python/federated -https://github.com/cynricfu/FedHGN -https://github.com/xiyuanyang45/DynamicPFL -https://github.com/haozhaowang/DaFKD2023 -https://github.com/Princeton-SysML/GradAttack -https://github.com/LatticeX-Foundation/Rosetta -https://github.com/xuchenhao001/AFL +https://github.com/exquisite1210/PT-FUCH_P +https://github.com/facebookresearch/FLSim +https://github.com/facebookresearch/canife +https://github.com/facebookresearch/dp_compression +https://github.com/facebookresearch/where_to_begin +https://github.com/farzanfarnia/RobustFL +https://github.com/fedego/fedego +https://github.com/fedlearnAI/fedlearn-algo +https://github.com/fio1982/FlexiFed +https://github.com/flair-thu/creamfl +https://github.com/flint-xf-fan/Byzantine-Federeated-RL +https://github.com/gamarcad/samba-demo +https://github.com/gaoliang13/FedDC https://github.com/garyxcheng/personalized-federated-learning -https://github.com/hangxu0304/DeepReduce -https://github.com/zhyczy/Fed-CO2 -https://github.com/FedML-AI/FedNLP -https://github.com/shenzebang/Federated-Learning-Pytorch -https://github.com/KAI-YUE/ntk-fed -https://github.com/Astuary/Flow -https://github.com/xidongwu/Federated-Minimax-and-Conditional-Stochastic-Optimization/tree/main -https://github.com/FengHZ/KD3A -https://github.com/TCtower/GlueFL -https://github.com/DeRafael/CAFE -https://github.com/chunmeifeng/FedPR -https://github.com/raymin0223/LoGo -https://github.com/google/fedjax -https://github.com/Di-Chai/FedEval -https://github.com/xidongwu/Federated-Minimax-and-Conditional-Stochastic-Optimization/ -https://github.com/Distributed-Learning-Networking-Group/FedMoS/ -https://github.com/OpenMined/PySyft -https://github.com/epfml/federated-learning-public-code/tree/master/codes/FedDF-code -https://github.com/TsingZ0/PFL-Non-IID -https://github.com/cyyever/distributed_learning_simulator -https://github.com/google-research/dataset_grouper -https://github.com/Chen-Junbao/SecureAggregation -https://github.com/microsoft/FedDrift -https://github.com/JYWa/FedNova -https://github.com/Yujun-Shi/FedCLS -https://github.com/Chung-ju/VFedTrans -https://github.com/Koukyosyumei/AIJack -https://github.com/wudonglei99/smartidx -https://github.com/TinfoilHat0/Defending-Against-Backdoors-with-Robust-Learning-Rate -https://github.com/pps-lab/rofl-project-code -https://github.com/HUST-EIC-AI-LAB/UCADI -https://github.com/vaseline555/superfed -https://github.com/xaynetwork/xaynet -https://github.com/NVIDIA/NVFlare/tree/main/research/one-shot-vfl -https://github.com/lx10077/fedavgpy -https://github.com/bibikar/feddst -https://github.com/Thinklab-SJTU/GAMF -https://github.com/APPFL/APPFL -https://github.com/andytu28/fps_pre-training -https://github.com/balanced-fl/Addressing-Class-Imbalance-FL -https://github.com/SonyAI/MocoSFL -https://github.com/Sungwon-Han/FEDCPA +https://github.com/garyzhang99/DM-PFL https://github.com/gcfgae/GCFGAE -https://github.com/purp1eHaze/FedIPR -https://github.com/WenkeHuang/FSMAFL +https://github.com/gdisag/gradient_disaggregation +https://github.com/ghafeleb/Private-NonConvex-Federated-Learning-Without-a-Trusted-Server +https://github.com/giemp95/feddti +https://github.com/gingsmith/fmtl +https://github.com/git-disl/Lockdown +https://github.com/git-disl/STDLens +https://github.com/git-disl/scale-fl +https://github.com/gkaissis/PriMIA +https://github.com/google-research/dataset_grouper +https://github.com/google-research/federated +https://github.com/google/fedjax +https://github.com/guopengf/Auto-FedRL +https://github.com/guopengf/FL-MRCM +https://github.com/guskarls/dfl-pens +https://github.com/hanguo97/expectation-propagation +https://github.com/hangxu0304/DeepReduce +https://github.com/haoyangliASTAPLE/3DFed +https://github.com/haoyuzhao123/coreset-vfl-codes +https://github.com/haozhaowang/DaFKD2023 +https://github.com/haozzh/FedCR +https://github.com/harliwu/fedagrac +https://github.com/harliwu/fedamd +https://github.com/hasakiXie123/FedCMR +https://github.com/hfzhang31/A3FL +https://github.com/hgh0545/graph-fraudster +https://github.com/hit-mdc/FedTSC-FedST +https://github.com/hmgxr128/MIFA_code/ +https://github.com/hongliny/FCO-ICML21 +https://github.com/hongliny/FedAc-NeurIPS20 +https://github.com/hongliny/sharp-bounds-for-fedavg-and-continuous-perspective +https://github.com/hongyouc/Fed-RoD +https://github.com/hongyouc/fedbe +https://github.com/huerdong/FedVert-Experiments +https://github.com/huweibo/Awesome-Federated-Learning-on-Graph-and-GNN-papers +https://github.com/hxwujinze/federated-deep-knowledge-tracing +https://github.com/hyhmia/DisTrans +https://github.com/iQua/flsim +https://github.com/ielab/2022-SIGIR-noniid-foltr +https://github.com/ignavierng/notears-admm +https://github.com/illidanlab/FADE +https://github.com/illidanlab/FOSTER +https://github.com/illidanlab/SplitMix +https://github.com/imguangyu/fedperfix +https://github.com/imkevinkuo/noisy-eval-in-fl +https://github.com/innovation-cat/Awesome-Federated-Machine-Learning +https://github.com/inspire-group/ModelPoisoning +https://github.com/insujeon/MetaVD +https://github.com/intel/openfl +https://github.com/international-explore/awesome-privacy-chinese +https://github.com/iwang05/FLuID +https://github.com/jackie840129/fedfr +https://github.com/jcwang123/fedlc +https://github.com/jd-9n/9nfl +https://github.com/jedmills/fedgbo +https://github.com/jeremy313/FL-WBC +https://github.com/jeremy313/Soteria +https://github.com/jhcknzzm/Federated-Learning-Backdoor/ +https://github.com/jhoon-oh/FedBABU +https://github.com/jialinyi94/doubly-stochastic-federataed-bandit +https://github.com/jianyizhang123/FLOP +https://github.com/jiayunz/fedalign +https://github.com/jichan3751/ifca +https://github.com/jinghuichen/focused-flip-federated-backdoor-attack +https://github.com/jinkyu032/FedMLB +https://github.com/jma78/FedGTF-EF +https://github.com/junyizhu-ai/confidence_aware_pfl +https://github.com/junyizhu-ai/surrogate_model_extension +https://github.com/jw9msjwjnpdrlfw/tsfl +https://github.com/kaiyuanmifen/FederatedNLP +https://github.com/kiddyboots216/CommEfficient +https://github.com/konstmish/rr_prox_fed +https://github.com/kpdonahue/model_sharing_games +https://github.com/krishnap25/FL_partial_personalization +https://github.com/kxzxvbk/Fling +https://github.com/lancopku/fedmnmt https://github.com/layer6ai-labs/ProxyFL -https://github.com/zlijingtao/ResSFL -https://github.com/FederatedAI/FedVision -https://github.com/divyansh03/fedexp -https://github.com/alibaba/Elastic-Federated-Learning-Solution/tree/FedAds -https://github.com/trucndt/ami -https://github.com/FedML-AI/FedCV -https://github.com/HKUST-KnowComp/FKGE -https://github.com/IBM/FedMA -https://github.com/Batool-Salehi/FL-based-Sector-Selection -https://github.com/innovation-cat/Awesome-Federated-Machine-Learning -https://github.com/corentingiraud/federated-learning-secure-aggregation -https://github.com/AntixK/FedDyn -https://github.com/giemp95/feddti -https://github.com/chaoyitud/LeadFL -https://github.com/IBM/federated-learning-lib -https://github.com/guopengf/Auto-FedRL -https://github.com/google-research/federated/tree/master/private_linear_compression -https://github.com/tj-kim/pFedDef_v1 -https://github.com/gamarcad/samba-demo +https://github.com/lebyni/PFA +https://github.com/lgcollins/FedRep +https://github.com/liboyue/beer +https://github.com/liecn/PyramidFL +https://github.com/liehe/byzantine-robust-noniid-optimizer +https://github.com/lingjuanlv/FPPDL +https://github.com/lins-lab/fedbr +https://github.com/liqi16/martfl +https://github.com/litian96/FedProx +https://github.com/litian96/ditto +https://github.com/litian96/fair_flearn +https://github.com/littlesunlxy/fedpu-torch +https://github.com/liuquande/FedDG-ELCFS +https://github.com/liyipeng00/convergence +https://github.com/ljaiverson/pFL-APPLE https://github.com/ljaiverson/pgfed -https://github.com/facebookresearch/where_to_begin -https://github.com/kxzxvbk/Fling -https://github.com/jianyizhang123/FLOP -https://github.com/git-disl/Lockdown -https://github.com/cap-ntu/FedReID -https://github.com/varnio/fedsim -https://github.com/sungwon-han/fedx -https://github.com/maiph123/verticalgnn -https://github.com/EasyFL-AI/EasyFL/tree/master/applications/mas +https://github.com/ljb121002/fednar +https://github.com/lkyddd/gradma https://github.com/llm-eff/FedPepTAO -https://github.com/xu-jingyi/fedcorr -https://github.com/SMILELab-FL/FedLegal -https://github.com/clu5/federated-conformal -https://github.com/jialinyi94/doubly-stochastic-federataed-bandit -https://github.com/Xtra-Computing/SimFL -https://github.com/ZFancy/SFAT -https://github.com/wwzzz/fedgs -https://github.com/wyjeong/FedWeIT -https://github.com/ml-postech/gradient-inversion-generative-image-prior -https://github.com/hxwujinze/federated-deep-knowledge-tracing +https://github.com/llpilla/energy-optimal-federated-learning +https://github.com/lokinko/Federated-Learning +https://github.com/lowya/private-federated-learning-without-a-trusted-server https://github.com/lunanbit/FedUL -https://github.com/sail-research/iba -https://github.com/visitworld123/fedfed -https://github.com/liyipeng00/convergence -https://github.com/huerdong/FedVert-Experiments -https://github.com/raipranav/fcl-fedseit -https://github.com/flint-xf-fan/Byzantine-Federeated-RL +https://github.com/luozhengquan/DFL +https://github.com/lwz001/FML-ST +https://github.com/lx10077/fedavgpy +https://github.com/lxcnju/FedRepo +https://github.com/lzcemma/RACE_Distance +https://github.com/maiph123/verticalgnn +https://github.com/matenure/federated_feature_fusion +https://github.com/maxencenoble/Differential-Privacy-for-Heterogeneous-Federated-Learning +https://github.com/maxinge8698/FedID +https://github.com/mc-nya/FedNest +https://github.com/mccorby/PhotoLabeller +https://github.com/med-air/FedBN +https://github.com/med-air/HarmoFL +https://github.com/melodi-lab/divfl +https://github.com/mengcz13/KDD2021_CNFGNN +https://github.com/microsoft/FedDrift +https://github.com/microsoft/msrflute +https://github.com/minglllli/CBAFed +https://github.com/mkhodak/fedex +https://github.com/ml-postech/gradient-inversion-generative-image-prior +https://github.com/ml-unito/federation_boosting +https://github.com/mlcommons/MedPerf +https://github.com/mmendiet/FedAlign +https://github.com/mmorafah/pacfl +https://github.com/morningD/FlexCFL +https://github.com/morningD/GrouProx +https://github.com/morningd/flexcfl +https://github.com/mtang724/Self-Balancing-Federated-Learning +https://github.com/mysteryresearcher/dasha +https://github.com/nds2022/SGBoost +https://github.com/nhatminh/FEDL-INFOCOM +https://github.com/nju-websoft/FedLU +https://github.com/nlokeshiisc/SFedAvg-AAAI21 +https://github.com/nlokeshiisc/sfedavg-aaai21 +https://github.com/nusdbsystem/falcon https://github.com/nusdbsystem/pivot -https://github.com/HuskyW/FFPA -https://github.com/zeyu-zh/TrustFL -https://github.com/MehdiSet/PerFedMask -https://github.com/shengchaochen82/metepfl -https://github.com/adap/flower -https://github.com/cyberthreat-datasets/ctdd-2021-os-syslogs -https://github.com/SEED-VT/FedDebug +https://github.com/omarfoq/FedEM +https://github.com/omarfoq/communication-in-cross-silo-fl +https://github.com/omarfoq/knn-per https://github.com/omarfoq/streaming-fl -https://github.com/CharlieDinh/pFedMe -https://github.com/BHui97/PrivateFL -https://github.com/littlesunlxy/fedpu-torch -https://github.com/JiahuaDong/FISS -https://github.com/JinheonBaek/FED-PUB -https://github.com/Accenture/Labs-Federated-Learning -https://github.com/MLOPTPSU/FedTorch -https://github.com/facebookresearch/FLSim -https://github.com/GalaxyLearning/GFL +https://github.com/optimization-ai/icml2023_fedxl +https://github.com/orionw/multilingual-federated-learning +https://github.com/osu-nlp-group/fl4semanticparsing +https://github.com/owkin/FLamby +https://github.com/owkin/sratta +https://github.com/pasquini-dario/eludingsecureaggregation +https://github.com/pengyang7881187/fedrl +https://github.com/peterhan91/Thorax_GAN +https://github.com/pierreHmbt/FedCP-QQ +https://github.com/pps-lab/rofl-project-code +https://github.com/primihub/primihub +https://github.com/privacytrustlab/ml_privacy_meter +https://github.com/purp1eHaze/FedIPR +https://github.com/qizhuang-qz/FedCSPC +https://github.com/raipranav/fcl-fedseit +https://github.com/ramshi236/Accelerated-Federated-Learning-Over-MAC-in-Heterogeneous-Networks +https://github.com/rand2ai/fedboost +https://github.com/rasmus-pagh/private-countsketch +https://github.com/raymin0223/LoGo +https://github.com/rdz98/fedrecattack +https://github.com/rithram/flynn +https://github.com/rlphilli/Collaborative-Incentives +https://github.com/rong-dai/DisPFL +https://github.com/royson/fedl2p/ +https://github.com/sabersalehk/MRE_C +https://github.com/sail-research/iba +https://github.com/saist1993/dpnlp +https://github.com/sarapieri/fed_het +https://github.com/scaleoutsystems/fedn +https://github.com/secretflow/secretflow +https://github.com/sfu-db/FedRain-and-Frog +https://github.com/shahakash28/simc +https://github.com/shams-sam/FedOptim +https://github.com/shangxinyi/CReFF-FL +https://github.com/shengchaochen82/metepfl +https://github.com/shenzebang/CENTAUR-Privacy-Federated-Representation-Learning +https://github.com/shenzebang/Federated-Learning-Pytorch +https://github.com/siquanhuang/Multi-metrics_against_backdoors_in_FL +https://github.com/songw-sw/f2l https://github.com/sparsefed/sparsefed -https://github.com/lxcnju/FedRepo -https://github.com/IntelligentNetworkingLAB/Graph-Neural-Network-based-Federated-Learning-for-Heterogenous-Device-Network -https://github.com/cuhksz-nlp/GCASeg -https://github.com/omarfoq/knn-per -https://github.com/citychan/federated-dpms +https://github.com/sungwon-han/fedx +https://github.com/sunjunaimer/TPAMI-LAQ +https://github.com/taokz/FedR +https://github.com/taoqi98/FedSampling +https://github.com/taoqi98/PrivateKT +https://github.com/teijyogen/secsv +https://github.com/tensorflow/federated +https://github.com/tfzhou/fedfa +https://github.com/tj-kim/pFedDef_v1 +https://github.com/totilas/padadmm +https://github.com/trucndt/ami +https://github.com/tsingz0/fedala +https://github.com/tsingz0/fedcp +https://github.com/unc-optimization/FedDR +https://github.com/usc-sail/fed-multimodal +https://github.com/varnio/fedsim +https://github.com/vaseline555/superfed +https://github.com/venkatesh-saligrama/Personalized-Federated-Learning +https://github.com/viktorvaladi/fedval +https://github.com/visitworld123/fedfed +https://github.com/vrt1shjwlkr/NDSS21-Model-Poisoning +https://github.com/wanglun1996/secure-robust-federated-learning +https://github.com/weimingwill/awesome-federated-learning +https://github.com/wenkehuang/fccl +https://github.com/wenzhu23333/Differential-Privacy-Based-Federated-Learning +https://github.com/wingter562/SAFA +https://github.com/wizard1203/VHL +https://github.com/wnma3mz/FedLMD +https://github.com/wnn2000/fednoro +https://github.com/wrh14/learning_to_invert +https://github.com/wuch15/FedAttack +https://github.com/wuch15/FedPerGNN +https://github.com/wudonglei99/smartidx +https://github.com/wwzzz/fedgs +https://github.com/wyjeong/FedMatch +https://github.com/wyjeong/FedWeIT +https://github.com/xaynetwork/xaynet +https://github.com/xidongwu/D-AUPRC +https://github.com/xidongwu/Federated-Minimax-and-Conditional-Stochastic-Optimization/ +https://github.com/xiyuanyang45/DynamicPFL +https://github.com/xj231/featureinference-vfl +https://github.com/xjiajiahao/federated-minimax +https://github.com/xkLi-Allen/FedGTA +https://github.com/xmed-lab/rscfed https://github.com/xqlin98/Fair-yet-Equal-CML -https://github.com/saist1993/dpnlp -https://github.com/LabeliaLabs/distributed-learning-contributivity -https://github.com/LipingYi/QSFL -https://github.com/chunmeifeng/fedins -https://github.com/NVIDIA/NVFlare +https://github.com/xu-jingyi/fedcorr +https://github.com/xuchenhao001/AFL +https://github.com/yasar-rehman/fedvssl +https://github.com/ybdai7/chameleon-durable-backdoor +https://github.com/ycao5602/KAFAL +https://github.com/ycruan/FedSoft https://github.com/yflyl613/fedrec -https://github.com/ebagdasa/backdoor_federated_learning -https://github.com/alibaba/FederatedScope/tree/backdoor-bench +https://github.com/yh-yao/FedGCN +https://github.com/yh-yao/FedRule +https://github.com/yjw1029/Efficient-FedRec +https://github.com/yjw1029/ua-fedrec +https://github.com/youngfish42/FL-paper-update-tracker +https://github.com/yuetan031/fedproto +https://github.com/yuetan031/fedstar +https://github.com/yutong-dai/fednh +https://github.com/yuxuanzhang0713/fedcsr https://github.com/yxdyc/pfedgate -https://github.com/lkyddd/gradma -https://github.com/LatticeX-Foundation/Rosetta/blob/master/doc/DEPLOYMENT.md -https://github.com/rithram/flynn -https://github.com/weimingwill/awesome-federated-learning -https://github.com/konstmish/rr_prox_fed -https://github.com/krishnap25/FL_partial_personalization -https://github.com/benggggggggg/fedgame -https://github.com/haoyuzhao123/coreset-vfl-codes -https://github.com/EasyFL-AI/EasyFL -https://github.com/owkin/sratta -https://github.com/google-research/federated/tree/7525c36324cb022bc05c3fce88ef01147cae9740/periodic_distribution_shift -https://github.com/mtang724/Self-Balancing-Federated-Learning -https://github.com/JianXu95/FedPAC -https://github.com/J1nqianChen/FedKA -https://github.com/google-research/federated/tree/master/generalization -https://github.com/NVIDIA/NVFlare/tree/dev/research/fed-ce -https://github.com/rlphilli/Collaborative-Incentives +https://github.com/yzhao062/anomaly-detection-resources +https://github.com/zaixizhang/FLDetector +https://github.com/zexilee/iccv-2023-fedetf +https://github.com/zexilee/icml-2023-fedlaw +https://github.com/zeyu-zh/TrustFL +https://github.com/zfan20/PFGNNPlus +https://github.com/zhangcx19/ijcai-23-pfedrec +https://github.com/zhanghangtao/poisoning-attack-on-fl +https://github.com/zhaohaoru/federated-clustering-of-bandits +https://github.com/zhenqincn/FedAPEN +https://github.com/zhuangdizhu/FedGen +https://github.com/zhuohangli/GGL +https://github.com/zhyczy/Fed-CO2 +https://github.com/zj-jayzhang/Federated-Class-Continual-Learning +https://github.com/zjukg/maker +https://github.com/zkhku/fedsage +https://github.com/zlijingtao/ResSFL +https://github.com/zlz0414/FedDAR +https://github.com/zshuai8/FedGMM_ICML2023