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

• THUMNLab / awesome-graph-ood
  Papers about out-of-distribution generalization on graphs.
  ☆167Updated 2 years ago
• zepengzhang / awesome-graph-structure-learning
  A collection of papers on Graph Structural Learning (GSL)
  ☆56Updated last year
• yihongma / CILG-Papers
  A curated list of papers and code related to class-imbalanced learning on graphs (CILG).
  ☆43Updated 9 months ago
• yongduosui / CAL
  [KDD 2022] "Causal Attention for Interpretable and Generalizable Graph Classification" by Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, X…
  ☆96Updated last year
• yanliang3612 / awesome-imbalanced-learning-on-graphs
  A repository contains a collection of resources and papers on Imbalance Learning On Graphs
  ☆92Updated 5 months ago
• QueuQ / CGLB
  ☆59Updated 11 months ago
• qitianwu / GraphOOD-EERM
  The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"
  ☆94Updated 2 years ago
• RecklessRonan / GloGNN
  ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily
  ☆45Updated 3 years ago
• SitaoLuan / ACM-GNN
  NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…
  ☆86Updated 11 months ago
• zjunet / DropMessage
  The implementation for DropMessage.
  ☆37Updated 2 years ago
• zjunet / GPF
  The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.
  ☆35Updated 2 years ago
• Amanda-Zheng / Awesome-Data-Centric-GraphML
  A collection of papers and resources about Data Centric Graph Machine Learning (DC-GML)
  ☆40Updated 2 years ago
• yixinliu233 / GREET
  [AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating
  ☆53Updated 2 years ago
• GSL-Benchmark / GSLB
  A comprehensive benchmark of Graph Structure Learning (NeurIPS 2023 Datasets and Benchmarks Track)
  ☆120Updated last year
• Graph-COM / GSAT
  [ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.
  ☆170Updated last year
• lsh0520 / RGCL
  Ratioanle-aware Graph Contrastive Learning codebase
  ☆44Updated 2 years ago
• ahxt / g-mixup
  [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification
  ☆105Updated last year
• Emory-Melody / awesome-graph-reduction
  [IJCAI 2024] Papers about graph reduction including graph coarsening, graph condensation, graph sparsification, graph summarization, etc.
  ☆167Updated last week
• RingBDStack / VIB-GSL
  Code for "Graph Structure Learning with Variational Information Bottleneck" published in AAAI 2022
  ☆37Updated 3 years ago
• LFhase / CIGA
  [NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs
  ☆116Updated 2 years ago
• EnyanDai / NRGNN
  Offical pytorch implementation of proposed NRGNN and Compared Methods in "NRGNN: Learning a Label Noise-Resistant Graph Neural Network on…
  ☆45Updated 3 years ago
• TimeLovercc / Awesome-Graph-Causal-Learning
  A list of Graph Causal Learning materials.
  ☆205Updated 9 months ago
• YuanchenBei / Awesome-Graph-Structure-Learning
  A curated list of papers on graph structure learning (GSL).
  ☆50Updated 10 months ago
• yixinliu233 / D2PT
  [KDD'23] Learning Strong Graph Neural Networks with Weak Information
  ☆43Updated 2 years ago
• Xtra-Computing / Awesome-Literature-ILoGs
  Awesome literature on imbalanced learning on graphs
  ☆75Updated last year
• yifeiacc / COSTA
  Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning
  ☆49Updated 2 years ago
• tengxiao1 / GraphACL
  GraphACL: Simple and Asymmetric Graph Contrastive Learning (NeurIPS 2023)
  ☆33Updated last year
• usail-hkust / Awesome-Causality-Inspired-GNNs
  An awesome collection of causality-inspired graph neural networks.
  ☆90Updated 11 months ago
• liujing1023 / Graph-based-Knowledge-Distillation
  Graph based Knowledge Distillation: A Survey
  ☆68Updated 2 years ago
• SukwonYun / LTE4G
  [CIKM 2023] Code for the paper "LTE4G: Long-Tail Experts for Graph Neural Networks"
  ☆40Updated 3 years ago