Alternatives and similar repositories for Awesome-Causality-Inspired-GNNs:

Users that are interested in Awesome-Causality-Inspired-GNNs are comparing it to the libraries listed below

• zepengzhang / awesome-graph-structure-learning
  A collection of papers on Graph Structural Learning (GSL)
  ☆54Updated last year
• yongduosui / CAL
  [KDD 2022] "Causal Attention for Interpretable and Generalizable Graph Classification" by Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, X…
  ☆86Updated last year
• YuanchenBei / Awesome-Graph-Structure-Learning
  A curated list of papers on graph structure learning (GSL).
  ☆43Updated 2 months ago
• chirag-agarwall / nifty
  Code for paper https://arxiv.org/abs/2102.13186
  ☆44Updated 3 years ago
• jma712 / GEAR
  ☆18Updated 2 years ago
• SitaoLuan / ACM-GNN
  NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…
  ☆76Updated 3 months ago
• TimeLovercc / Awesome-Graph-Causal-Learning
  A list of Graph Causal Learning materials.
  ☆191Updated last month
• fannie1208 / CaNet
  [WWW2024 Oral paper] "Graph Out-of-Distribution Generalization via Causal Intervention”.
  ☆23Updated 4 months ago
• cshhzhao / GCOPE
  Official implementation of 'All in One and One for All: A Simple yet Effective Method towards Cross-domain Graph Pretraining' published i…
  ☆32Updated 4 months ago
• QueuQ / CGLB
  ☆55Updated 4 months ago
• NineAbyss / ZeroG
  The official implement of SIGKDD'24 paper: ZeroG: Investigating Cross-dataset Zero-shot Transferability in Graphs
  ☆28Updated 7 months ago
• jma712 / GraphCFE
  ☆16Updated last year
• CongWeilin / GraphMixer
  ☆99Updated last year
• wondergo2017 / DIDA
  Implementation Codes for NeurIPS22 paper "Dynamic Graph Neural Networks Under Spatio-Temporal Distribution Shift"
  ☆19Updated 2 years ago
• qitianwu / GraphOOD-EERM
  The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"
  ☆85Updated 2 years ago
• ZijieH / CG-ODE
  ☆35Updated 3 years ago
• yushundong / EDITS
  Open source code for paper "EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks".
  ☆26Updated 2 years ago
• qiaoyu-tan / S2GAE
  ☆48Updated 2 years ago
• zaixizhang / ProtGNN
  Official implementation of AAAI'22 paper "ProtGNN: Towards Self-Explaining Graph Neural Networks"
  ☆50Updated 2 years ago
• YesLab-Code / HTGNN
  ☆52Updated 3 years ago
• EdisonLeeeee / Awesome-Fair-Graph-Learning
  Paper List for Fair Graph Learning (FairGL).
  ☆134Updated 6 months ago
• Juanhui28 / HeaRT
  ☆52Updated 5 months ago
• EnyanDai / awesome-turstworthy-graph-neural-networks
  ☆24Updated 2 years ago
• yushundong / PyGDebias
  Open-source Library PyGDebias: Graph Datasets and Fairness-Aware Graph Mining Algorithms
  ☆62Updated 10 months ago
• HKUDS / GraphST
  [ICML'2023] "GraphST: Spatial-Temporal Graph Learning with Adversarial Contrastive Adaptation"
  ☆54Updated 2 months ago
• RecklessRonan / GloGNN
  ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily
  ☆43Updated 2 years ago
• ivam-he / ChebNetII
  PyTorch implementation of "Convolutional Neural Networks on Graphs with Chebyshev Approximation, Revisited"
  ☆35Updated last year
• BUPT-GAMMA / Uncovering-the-Structural-Fairness-in-Graph-Contrastive-Learning
  Source code for NeurIPS 2022 paper "Uncovering the Structural Fairness in Graph Contrastive Learning"
  ☆29Updated 2 years ago
• THUMNLab / awesome-graph-ood
  Papers about out-of-distribution generalization on graphs.
  ☆166Updated last year
• Emory-Melody / GraphSlim
  A Python library for graph reduction including condensation, coarsening, and sparsification.
  ☆17Updated last week