Alternatives and similar repositories for Awesome-Graph-Causal-Learning

Users that are interested in Awesome-Graph-Causal-Learning are comparing it to the libraries listed below

• usail-hkust / Awesome-Causality-Inspired-GNNs
  An awesome collection of causality-inspired graph neural networks.
  ☆93Updated 11 months ago
• THUMNLab / awesome-graph-ood
  Papers about out-of-distribution generalization on graphs.
  ☆167Updated 2 years ago
• yongduosui / CAL
  [KDD 2022] "Causal Attention for Interpretable and Generalizable Graph Classification" by Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, X…
  ☆97Updated 2 years ago
• TrustAGI-Lab / SUBLIME
  [WWW'22] Towards Unsupervised Deep Graph Structure Learning
  ☆143Updated 2 years ago
• Wuyxin / DIR-GNN
  (ICLR 2022) Discovering Invariant Rationales for Graph Neural Networks
  ☆133Updated 2 years ago
• YesLab-Code / HTGNN
  ☆63Updated 4 years ago
• jma712 / HyperSCI
  ☆45Updated last year
• MingChen-Sun / GPPT
  ☆60Updated 3 years ago
• zepengzhang / awesome-graph-structure-learning
  A collection of papers on Graph Structural Learning (GSL)
  ☆56Updated last year
• chirag-agarwall / nifty
  Code for paper https://arxiv.org/abs/2102.13186
  ☆43Updated 4 years ago
• EdisonLeeeee / Awesome-Fair-Graph-Learning
  Paper List for Fair Graph Learning (FairGL).
  ☆142Updated last year
• kaize0409 / awesome-graph-data-augmentaion
  A curated list of publications and code about data augmentaion for graphs.
  ☆63Updated 3 years ago
• Graph-COM / GSAT
  [ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.
  ☆171Updated last year
• Xtra-Computing / Awesome-Literature-ILoGs
  Awesome literature on imbalanced learning on graphs
  ☆75Updated last year
• jma712 / GraphCFE
  ☆17Updated 5 months ago
• zhao-tong / graph-data-augmentation-papers
  A curated list of graph data augmentation papers.
  ☆314Updated last year
• squareRoot3 / Rethinking-Anomaly-Detection
  "Rethinking Graph Neural Networks for Anomaly Detection" in ICML 2022
  ☆192Updated last year
• YuanchenBei / Awesome-Graph-Structure-Learning
  A curated list of papers on graph structure learning (GSL).
  ☆50Updated 10 months ago
• GSL-Benchmark / GSLB
  A comprehensive benchmark of Graph Structure Learning (NeurIPS 2023 Datasets and Benchmarks Track)
  ☆120Updated last year
• EnyanDai / awesome-turstworthy-graph-neural-networks
  ☆25Updated 3 years ago
• yushundong / PyGDebias
  Open-source Library PyGDebias: Graph Datasets and Fairness-Aware Graph Mining Algorithms
  ☆65Updated last year
• CongWeilin / GraphMixer
  ☆103Updated 2 years ago
• LFhase / CIGA
  [NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs
  ☆117Updated 2 years ago
• doujiang-zheng / Dynamic-Temporal-Graph-Learning-Reading-List
  Advances on machine learning of dynamic (temporal) graphs, covering the reading list of recent top academic conferences.
  ☆63Updated 2 years ago
• yuwvandy / FairVGNN
  ☆27Updated 3 years ago
• logseminar / Schedule
  Schedule for learning on graphs seminar
  ☆109Updated 2 years ago
• DM2-ND / CFLP
  Author: Tong Zhao (tzhao2@nd.edu). ICML 2022. Learning from Counterfactual Links for Link Prediction
  ☆71Updated 3 years ago
• ahxt / g-mixup
  [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification
  ☆105Updated last year
• flyingdoog / PTDNet
  Learning to Drop: Robust Graph Neural Network via Topological Denoising & Robust Graph Representation Learning via Neural Sparsification
  ☆81Updated 4 years ago
• SitaoLuan / LLM4Graph
  ☆186Updated last year