Alternatives and similar repositories for CAF-GNN

Users that are interested in CAF-GNN are comparing it to the libraries listed below

• THUMNLab / awesome-graph-ood
  Papers about out-of-distribution generalization on graphs.
  ☆168Updated 2 years ago
• zepengzhang / awesome-graph-structure-learning
  A collection of papers on Graph Structural Learning (GSL)
  ☆58Updated 2 years ago
• jma712 / GEAR
  ☆18Updated 3 years ago
• XweiQ / Benchmark-GraphFairness
  The repository of "Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark" (KDD'24)
  ☆13Updated last year
• Data-Centric-GraphML / awesome-papers
  A collection of papers and resources about Data-centric Graph Machine Learning (DC-GML).
  ☆46Updated 2 years ago
• NineAbyss / GLBench
  The official implement of NeurIPS'24 Datasets and Benchmarks Track paper: GLBench: A Comprehensive Benchmark for Graphs with Large Langua…
  ☆70Updated last year
• CurryTang / LLMGNN
  Label-free Node Classification on Graphs with Large Language Models (LLMS)
  ☆91Updated 2 years ago
• tengxiao1 / Awesome-Graph-Contrastive-Learning-with-Heterophily
  Papers about Graph Contrastive Learning and Graph Self-supervised Learning on Graphs with Heterophily
  ☆38Updated 2 years ago
• yushundong / PyGDebias
  Open-source Library PyGDebias: Graph Datasets and Fairness-Aware Graph Mining Algorithms
  ☆65Updated last year
• LechengKong / OneForAll
  A fundational graph learning framework that solves cross-domain/cross-task classification problems using one model.
  ☆241Updated last year
• CurryTang / TSGFM
  NIPS 24: Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights
  ☆48Updated last year
• ZhuYun97 / GraphCLIP
  Official implementation of GraphCLIP: Enhancing Transferability in Graph Foundation Models for Text-Attributed Graphs
  ☆65Updated 10 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…
  ☆45Updated last year
• EdisonLeeeee / Awesome-Fair-Graph-Learning
  Paper List for Fair Graph Learning (FairGL).
  ☆144Updated last year
• YuanchenBei / Awesome-Graph-Structure-Learning
  A curated list of papers on graph structure learning (GSL).
  ☆52Updated last year
• SitaoLuan / LLM4Graph
  ☆186Updated last year
• HaitaoMao / Awesome_Graph_Foundation_Models
  Accompanied repositories for our paper Graph foundation model
  ☆230Updated last year
• AndyJZhao / GLEM
  ☆133Updated 9 months ago
• GSL-Benchmark / GSLB
  A comprehensive benchmark of Graph Structure Learning (NeurIPS 2023 Datasets and Benchmarks Track)
  ☆123Updated last year
• VITA-Group / LLaGA
  [ICML2024] "LLaGA: Large Language and Graph Assistant", Runjin Chen, Tong Zhao, Ajay Jaiswal, Neil Shah, Zhangyang Wang
  ☆148Updated last year
• zjunet / GPF
  The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.
  ☆37Updated 2 years ago
• NineAbyss / ZeroG
  The official implement of SIGKDD'24 paper: ZeroG: Investigating Cross-dataset Zero-shot Transferability in Graphs
  ☆35Updated last year
• ChandlerBang / GTrans
  [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"
  ☆65Updated 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…
  ☆53Updated 8 months ago
• CurryTang / Towards-graph-foundation-models
  ☆91Updated 2 years ago
• AndrewZhou924 / Awesome-Graph-Prompting
  A curated list of resources for graph prompting methods
  ☆29Updated last year
• yanliang3612 / awesome-imbalanced-learning-on-graphs
  A repository contains a collection of resources and papers on Imbalance Learning On Graphs
  ☆94Updated 7 months ago
• tengxiao1 / GraphACL
  GraphACL: Simple and Asymmetric Graph Contrastive Learning (NeurIPS 2023)
  ☆34Updated last year
• rollingstonezz / Curriculum_learning_for_GNNs
  This is the official repository for NeurIPS 2023 paper "Curriculum Learning for Graph Neural Networks: Which Edges Should We Learn First"
  ☆17Updated 2 years ago
• NYUSHCS / GAugLLM
  Open Source Code for GAugLLM: Improving Graph Contrastive Learning for Text-Attributed Graphs with Large Language Models (KDD'24)
  ☆28Updated last year