OnlyJerryLee

OnlyJerryLee's Stars

• microsoft/Graphormer

  Graphormer is a general-purpose deep learning backbone for molecular modeling.

  Language:Python2.1k331

• PonderLY/PC-GNN

  (WWW 2021) Source code of PC-GNN

  Language:Python9521

• he-tiantian/CATs-Learning-Conjoint-Attentions-for-Graph-Neural-Nets

  Learning Conjoint Attentions for Graph Neural Nets, NeurIPS 2021

  5

• JoonHyung-Park/GraphENS

  GraphENS: Neighbor-Aware Ego Network Synthesis for Class-Imbalanced Node Classification (ICLR'22)

  Language:Python747

• CastalZhou/graphsr

  Language:Python72

• victorchen96/ReNode

  Code for Neurips2021 Paper "Topology-Imbalance Learning for Semi-Supervised Node Classification".

  Language:Python558

• sunxiaobei/awesome-attention-based-gnns

  A collection of resources on attention-based graph neural networks

  4411

• inyeoplee77/SAGPool

  Official PyTorch Implementation of SAGPool - ICML 2019

  Language:Python35980

• TianxiangZhao/GraphSmote

  Pytorch implementation of paper 'GraphSMOTE: Imbalanced Node Classification on Graphs with Graph Neural Networks' to appear on WSDM2021

  Language:Python14529

• THUDM/GCC

  GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training @ KDD 2020

  Language:Python32153

• Shen-Lab/SS-GCNs

  [ICML 2020] "When Does Self-Supervision Help Graph Convolutional Networks?" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen

  Language:Python10727

• snap-stanford/pretrain-gnns

  Strategies for Pre-training Graph Neural Networks

  Language:Python955161

• chennnM/GCNII

  PyTorch implementation of "Simple and Deep Graph Convolutional Networks"

  Language:Python32072

• DropEdge/DropEdge

  This is a Pytorch implementation of paper: DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

  Language:Python46972

• dongkwan-kim/SuperGAT

  [ICLR 2021] How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision

  Language:Python15026

• jwzhanggy/Graph-Bert

  Source code of Graph-Bert

  Language:Python46784

• lehaifeng/T-GCN

  Temporal Graph Convolutional Network for Urban Traffic Flow Prediction Method

  Language:Jupyter Notebook1.4k435

• lmy1997/tuxiaoshi

  Language:Python17615

• ronghangzhu/CensNet

  Language:Python6511

• THUDM/GRAND-plus

  Code and dataset for paper "GRAND+: Scalable Graph Random Neural Networks"

  Language:Python302

• hengruizhang98/GRAND

  DGL implementation of GRAND(Graph Random Neural Network, NeurIPS 2020)

  Language:Python163

• vikasverma1077/GraphMix

  Code for reproducing results in GraphMix paper

  Language:Python7114

• waimorris/E-GraphSAGE

  A PyTorch implementation of of E-GraphSAGE.

  Language:Jupyter Notebook6716

• hoangntc/TS-IDS

  Language:Jupyter Notebook13

• weihua916/powerful-gnns

  How Powerful are Graph Neural Networks?

  Language:Python1.2k222

• tech-srl/how_attentive_are_gats

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

  Language:Python29937

• renj-xu/NEGSC

  NEGSC

  Language:Jupyter Notebook204

• George730/E-ResGAT

  The pytorch implementation of E-GraphSAGE and E-ResGAT, two solutions for intrusion detection.

  Language:Jupyter Notebook6328

• jwwthu/GNN-Communication-Networks

  This is the repository for the collection of Graph-based Deep Learning for Communication Networks.

  38268

• THUDM/GRAND

  Source code and dataset of the NeurIPS 2020 paper "Graph Random Neural Network for Semi-Supervised Learning on Graphs"

  Language:Python20140