devnkong / FLAG

Related projects: ⓘ

• snap-stanford / GIB
  Graph Information Bottleneck (GIB) for learning minimal sufficient structural and feature information using GNNs
  ☆123Updated last year
• AaltoPML / Rethinking-pooling-in-GNNs
  ☆60Updated 3 years ago
• ChandlerBang / GCond
  [ICLR'22] [KDD'22] [IJCAI'24] Implementation of "Graph Condensation for Graph Neural Networks"
  ☆115Updated 2 months ago
• mims-harvard / G-Meta
  Graph meta learning via local subgraphs (NeurIPS 2020)
  ☆119Updated last month
• Shen-Lab / SS-GCNs
  [ICML 2020] "When Does Self-Supervision Help Graph Convolutional Networks?" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen
  ☆107Updated 3 years ago
• CUAI / Non-Homophily-Benchmarks
  [WWW 2021 GLB] New Benchmarks for Learning on Non-Homophilous Graphs
  ☆111Updated 2 years ago
• zpeng27 / GMI
  Graph Representation Learning via Graphical Mutual Information Maximization
  ☆109Updated 4 years ago
• jianhao2016 / GPRGNN
  ☆128Updated last year
• lxiaorui / ElasticGNN
  Official implementation of the ICML2021 paper "Elastic Graph Neural Networks"
  ☆40Updated 3 years ago
• nerdslab / bgrl
  PyTorch implementation of BGRL (https://arxiv.org/abs/2102.06514)
  ☆79Updated last year
• GemsLab / H2GCN
  Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)
  ☆96Updated 2 years ago
• Shen-Lab / GraphCL_Automated
  [ICML 2021] "Graph Contrastive Learning Automated" by Yuning You, Tianlong Chen, Yang Shen, Zhangyang Wang; [WSDM 2022] "Bringing Yo…
  ☆108Updated last week
• ChandlerBang / SelfTask-GNN
  Implementation of paper "Self-supervised Learning on Graphs:Deep Insights and New Directions"
  ☆94Updated last year
• hugochan / IDGL
  Code & data accompanying the NeurIPS 2020 paper "Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddin…
  ☆219Updated last year
• tech-srl / bottleneck
  Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"
  ☆91Updated 2 years ago
• LingxiaoShawn / PairNorm
  Source code for PairNorm (ICLR 2020)
  ☆77Updated 4 years ago
• mengliu1998 / DL4DisassortativeGraphs
  Papers about developing DL methods on disassortative graphs
  ☆48Updated 2 years ago
• susheels / adgcl
  Adversarial Graph Augmentation to Improve Graph Contrastive Learning
  ☆82Updated 2 years ago
• flyingdoog / PGExplainer
  Parameterized Explainer for Graph Neural Network
  ☆123Updated 6 months ago
• vikasverma1077 / GraphMix
  Code for reproducing results in GraphMix paper
  ☆71Updated last year
• ahxt / g-mixup
  [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification
  ☆90Updated 6 months ago
• LFhase / CIGA
  [NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs
  ☆97Updated last year
• Kaixiong-Zhou / DGN
  Pytorch implementation of differentiable group normalization (NeurIPS 2020)
  ☆37Updated 3 years ago
• THUDM / grb
  Graph Robustness Benchmark: A scalable, unified, modular, and reproducible benchmark for evaluating the adversarial robustness of Graph M…
  ☆91Updated 10 months ago
• LarsHoldijk / RE-ParameterizedExplainerForGraphNeuralNetworks
  ☆51Updated 2 years ago
• mims-harvard / GNNGuard
  Defending graph neural networks against adversarial attacks (NeurIPS 2020)
  ☆57Updated last year
• BorealisAI / SLAPS-GNN
  PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"
  ☆85Updated 2 years ago
• qitianwu / GraphOOD-EERM
  The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"
  ☆80Updated last year
• THUDM / GRAND
  Source code and dataset of the NeurIPS 2020 paper "Graph Random Neural Network for Semi-Supervised Learning on Graphs"
  ☆202Updated last year
• facebookresearch / shaDow_GNN
  NeurIPS 2021: Improve the GNN expressivity and scalability by decoupling the depth and receptive field of state-of-the-art GNN architectu…
  ☆133Updated 2 years ago