Alternatives and similar repositories for contrastive-gnn-explanation

Users that are interested in contrastive-gnn-explanation are comparing it to the libraries listed below

• flyingdoog / PGExplainer
  Parameterized Explainer for Graph Neural Network
  ☆141Updated last year
• WilliamCCHuang / GraphLIME
  This is a Pytorch implementation of GraphLIME
  ☆94Updated 3 years ago
• danielzuegner / robust-gcn
  Implementation of the paper "Certifiable Robustness and Robust Training for Graph Convolutional Networks".
  ☆43Updated 5 years ago
• zpeng27 / GMI
  Graph Representation Learning via Graphical Mutual Information Maximization
  ☆118Updated 5 years ago
• wanyu-lin / ICML2021-Gem
  Official code for the ICML 2021 paper "Generative Causal Explanations for Graph Neural Networks."
  ☆67Updated 3 years ago
• BorgwardtLab / WWL
  Wasserstein Weisfeiler-Lehman Graph Kernels
  ☆86Updated last year
• vunhatminh / PGMExplainer
  Generating PGM Explanation for GNN predictions
  ☆76Updated 2 years ago
• devnkong / FLAG
  Official implementation of our FLAG paper (CVPR2022)
  ☆145Updated 3 years ago
• marblet / GCNmf
  PyTorch implementation of "Graph Convolutional Networks for Graphs Containing Missing Features"
  ☆48Updated last year
• chirag-agarwall / nifty
  Code for paper https://arxiv.org/abs/2102.13186
  ☆43Updated 4 years ago
• a-lucic / cf-gnnexplainer
  ☆63Updated last week
• hugochan / IDGL
  Code & data accompanying the NeurIPS 2020 paper "Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddin…
  ☆234Updated 2 years ago
• GentleZhu / Shift-Robust-GNNs
  "Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data" (NeurIPS 21')
  ☆49Updated 3 years ago
• Kaixiong-Zhou / DGN
  Pytorch implementation of differentiable group normalization (NeurIPS 2020)
  ☆38Updated 5 years ago
• zaixizhang / ProtGNN
  Official implementation of AAAI'22 paper "ProtGNN: Towards Self-Explaining Graph Neural Networks"
  ☆50Updated 3 years ago
• THUDM / grb
  Graph Robustness Benchmark: A scalable, unified, modular, and reproducible benchmark for evaluating the adversarial robustness of Graph M…
  ☆98Updated 2 years ago
• susheels / adgcl
  Adversarial Graph Augmentation to Improve Graph Contrastive Learning
  ☆92Updated 4 years ago
• vikasverma1077 / GraphMix
  Code for reproducing results in GraphMix paper
  ☆72Updated 3 years ago
• mims-harvard / GNNGuard
  Defending graph neural networks against adversarial attacks (NeurIPS 2020)
  ☆71Updated 2 years ago
• ChandlerBang / SimP-GCN
  Implementation of the WSDM 2021 paper "Node Similarity Preserving Graph Convolutional Networks"
  ☆59Updated 4 years ago
• chentingpc / gfn
  Code for "Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification"
  ☆53Updated 5 years ago
• BorealisAI / SLAPS-GNN
  PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"
  ☆89Updated 4 years ago
• snap-stanford / GIB
  Graph Information Bottleneck (GIB) for learning minimal sufficient structural and feature information using GNNs
  ☆138Updated 3 years ago
• Graph-COM / GSAT
  [ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.
  ☆173Updated last year
• CUAI / Non-Homophily-Benchmarks
  [WWW 2021 GLB] New Benchmarks for Learning on Non-Homophilous Graphs
  ☆116Updated 4 years ago
• GemsLab / H2GCN
  Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)
  ☆107Updated 6 months ago
• LarsHoldijk / RE-ParameterizedExplainerForGraphNeuralNetworks
  ☆55Updated 3 years ago
• mims-harvard / G-Meta
  Graph meta learning via local subgraphs (NeurIPS 2020)
  ☆126Updated last year
• vanoracai / MixupForGraph
  Code for paper "Mixup for Node and Graph Classification", WWW 2021
  ☆47Updated 4 years ago
• russchua / Graph-Isomorphism-Networks
  A Tensorflow 2.0 implementation of Graph Isomorphism Networks.
  ☆55Updated 6 years ago