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
• fannie1208 / CaNet
  [WWW2024 Oral paper] "Graph Out-of-Distribution Generalization via Causal Intervention”.
  ☆25Updated 6 months ago
• yongduosui / CAL
  [KDD 2022] "Causal Attention for Interpretable and Generalizable Graph Classification" by Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, X…
  ☆89Updated last year
• TimeLovercc / Awesome-Graph-Causal-Learning
  A list of Graph Causal Learning materials.
  ☆195Updated 3 months ago
• qitianwu / GraphOOD-EERM
  The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"
  ☆87Updated 2 years ago
• YuanchenBei / Awesome-Graph-Structure-Learning
  A curated list of papers on graph structure learning (GSL).
  ☆48Updated 3 months ago
• wondergo2017 / DIDA
  Implementation Codes for NeurIPS22 paper "Dynamic Graph Neural Networks Under Spatio-Temporal Distribution Shift"
  ☆20Updated 2 years ago
• CongWeilin / GraphMixer
  ☆99Updated last year
• ZijieH / CG-ODE
  ☆36Updated 3 years ago
• QueuQ / CGLB
  ☆56Updated 5 months ago
• NineAbyss / ZeroG
  The official implement of SIGKDD'24 paper: ZeroG: Investigating Cross-dataset Zero-shot Transferability in Graphs
  ☆28Updated 8 months ago
• chirag-agarwall / nifty
  Code for paper https://arxiv.org/abs/2102.13186
  ☆44Updated 4 years ago
• SitaoLuan / ACM-GNN
  NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…
  ☆80Updated 5 months ago
• jma712 / GraphCFE
  ☆17Updated last year
• RingBDStack / VIB-GSL
  Code for "Graph Structure Learning with Variational Information Bottleneck" published in AAAI 2022
  ☆35Updated 2 years ago
• Skyorca / Awesome-Graph-Domain-Adaptation-Papers
  Published papers focusing on graph domain adaptation, with survey paper online as Domain Adaptation for Graph Representation Learning: Ch…
  ☆41Updated this week
• Emory-Melody / Awesome-Graph-Neural-Differential-Equations
  Paper list on GNNs + Differential Equations (ODE, PDE, SDE)
  ☆17Updated 3 weeks ago
• saper0 / adversarial_training
  Codebase used to generate the results for NeurIPS23 "Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directi…
  ☆11Updated last year
• qiaoyu-tan / S2GAE
  ☆47Updated 2 years ago
• YesLab-Code / HTGNN
  ☆52Updated 3 years ago
• jma712 / GEAR
  ☆18Updated 3 years ago
• THUMNLab / awesome-graph-ood
  Papers about out-of-distribution generalization on graphs.
  ☆167Updated last year
• EnyanDai / awesome-turstworthy-graph-neural-networks
  ☆24Updated 2 years ago
• ivam-he / ChebNetII
  PyTorch implementation of "Convolutional Neural Networks on Graphs with Chebyshev Approximation, Revisited"
  ☆38Updated last year
• cshhzhao / GCOPE
  Official implementation of 'All in One and One for All: A Simple yet Effective Method towards Cross-domain Graph Pretraining' published i…
  ☆35Updated 6 months ago
• ahxt / g-mixup
  [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification
  ☆103Updated last year
• RManLuo / GSNOP
  Official code implementation for WSDM 23 paper Graph Sequential Neural ODE Process for Link Prediction on Dynamic and Sparse Graphs.
  ☆33Updated last year
• Graph-COM / GSAT
  [ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.
  ☆167Updated last year
• squareRoot3 / GADBench
  "GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection" in NeurIPS 2023
  ☆111Updated 10 months ago
• chr26195 / PMLP
  This is the official code repository for "Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs", wh…
  ☆88Updated 10 months ago