Alternatives and similar repositories for Awesome-Graph-Domain-Adaptation-Papers

Users that are interested in Awesome-Graph-Domain-Adaptation-Papers 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…
  ☆90Updated last year
• qitianwu / GraphOOD-EERM
  The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"
  ☆89Updated 2 years ago
• THUMNLab / awesome-graph-ood
  Papers about out-of-distribution generalization on graphs.
  ☆166Updated 2 years ago
• QueuQ / CGLB
  ☆57Updated 7 months ago
• tengxiao1 / GraphACL
  GraphACL: Simple and Asymmetric Graph Contrastive Learning (NeurIPS 2023)
  ☆31Updated last year
• Graph-COM / StruRW
  [ICML 2023] Structural Re-weighting Improves Graph Domain Adaptation (StruRW)
  ☆21Updated 2 years ago
• zjunet / GPF
  The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.
  ☆31Updated last year
• tengxiao1 / Awesome-Graph-Contrastive-Learning-with-Heterophily
  Papers about Graph Contrastive Learning and Graph Self-supervised Learning on Graphs with Heterophily
  ☆37Updated last year
• yixinliu233 / D2PT
  [KDD'23] Learning Strong Graph Neural Networks with Weak Information
  ☆42Updated 2 years ago
• ahxt / g-mixup
  [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification
  ☆105Updated last year
• yixinliu233 / G-OOD-D
  [WSDM'23] GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection
  ☆42Updated 2 years ago
• CurryTang / TSGFM
  NIPS 24: Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights
  ☆44Updated 6 months ago
• RingBDStack / VIB-GSL
  Code for "Graph Structure Learning with Variational Information Bottleneck" published in AAAI 2022
  ☆37Updated 3 years 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…
  ☆39Updated 8 months ago
• RecklessRonan / GloGNN
  ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily
  ☆43Updated 2 years ago
• Newiz430 / Pretext
  Resource for "A Survey on Self-Supervised Graph Foundation Models: Knowledge-Based Perspective"
  ☆34Updated last month
• NineAbyss / ZeroG
  The official implement of SIGKDD'24 paper: ZeroG: Investigating Cross-dataset Zero-shot Transferability in Graphs
  ☆31Updated 10 months ago
• fannie1208 / CaNet
  [WWW2024 Oral paper] "Graph Out-of-Distribution Generalization via Causal Intervention”.
  ☆25Updated 8 months ago
• lsh0520 / RGCL
  Ratioanle-aware Graph Contrastive Learning codebase
  ☆43Updated 2 years ago
• wenzhilics / GraphSHA
  "GraphSHA: Synthesizing Harder Samples for Class-Imbalanced Node Classification" in KDD'23
  ☆30Updated last year
• yixinliu233 / GREET
  [AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating
  ☆52Updated 2 years ago
• SitaoLuan / ACM-GNN
  NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…
  ☆83Updated 7 months ago
• Amanda-Zheng / SFGC
  Pytorch implementation of NeurIPS-23:"Structure-free Graph Condensation (SFGC): From Large-scale Graphs to Condensed Graph-free Data"
  ☆36Updated 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
• yifeiacc / COSTA
  Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning
  ☆49Updated 2 years ago
• YuanchenBei / Awesome-Graph-Transfer-Learning
  A curated list of papers on graph transfer learning (GTL).
  ☆17Updated last year
• EnyanDai / NRGNN
  Offical pytorch implementation of proposed NRGNN and Compared Methods in "NRGNN: Learning a Label Noise-Resistant Graph Neural Network on…
  ☆42Updated 2 years ago
• liun-online / CoGSL
  Official Code: TheWebConf 2022 Compact Graph Structure Learning via Mutual Information Compression
  ☆24Updated last year
• chr26195 / PMLP
  This is the official code repository for "Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs", wh…
  ☆88Updated last year