My implementation of the original GAT paper (Veličković et al.). I've additionally included the playground.py file for visualizing the Cora dataset, GAT embeddings, an attention mechanism, and entropy histograms. I've supported both Cora (transductive) and PPI (inductive) examples!

Implementation and experiments of graph neural netwokrs, like gcn,graphsage,gat,etc.

[ICLR 2020; IPDPS 2019] Fast and accurate minibatch training for deep GNNs and large graphs (GraphSAINT: Graph Sampling Based Inductive Learning Method).

Code for the paper "How Attentive are Graph Attention Networks?" (ICLR'2022)

Multi-turn dialogue baselines written in PyTorch

B站GNN教程资料

This is a PyTorch implementation of the GeniePath model in <GeniePath: Graph Neural Networks with Adaptive Receptive Paths> (https://arxiv.org/abs/1802.00910)

中华人民共和国国家标准文档

PyTorch code for ICPR 2020 paper "DAG-Net: Double Attentive Graph Neural Network for Trajectory Forecasting"

GNN方法和模型的Pytorch实现。Pytorch implementation of GNN.

Graph Neural Networks

Browedit is an editor for rsw, gnd and gat files

Gradient gating (ICLR 2023)

PyTorch implementation of the Graph Attention Networks (GAT) based on the paper "Graph Attention Network" by Velickovic et al - https://arxiv.org/abs/1710.10903v3

[NLPCC 2020] Sentence Constituent-Aware Aspect-Category Sentiment Analysis with Graph Attention Networks

Graph Convolutional Networks, Graph Attention Networks, Gated Graph Neural Net, Mixhop

My solutions for Stanford University course CS224W: Machine Learning with Graphs Fall 2021 colabs (GNN, GAT, GraphSAGE, GCN)

玩转图神经网络和知识图谱的相关算法：GCN,GAT,GAFM,GAAFM,GraphSage,W2V,TRANSe

Transformer implemented with graph attention network (GAT) layers from PyTorch Geometric

PyTorch implementation of GNN models