Alternatives and similar repositories for CoGSL:

Users that are interested in CoGSL are comparing it to the libraries listed below

• yixinliu233 / GREET
  [AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating
  ☆52Updated 2 years ago
• RecklessRonan / GloGNN
  ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily
  ☆43Updated 2 years ago
• BUPT-GAMMA / Graph-Structure-Estimation-Neural-Networks
  Source code for WWW 2021 paper "Graph Structure Estimation Neural Networks"
  ☆58Updated 3 years ago
• tengxiao1 / GraphACL
  GraphACL: Simple and Asymmetric Graph Contrastive Learning (NeurIPS 2023)
  ☆30Updated 9 months ago
• LuckyTiger123 / GPF
  The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.
  ☆22Updated last year
• lsh0520 / RGCL
  Ratioanle-aware Graph Contrastive Learning codebase
  ☆40Updated last year
• zjs123 / DTGB
  Comprehensive Benchmark Dataset for Dynamic Text-Attributed Graphs
  ☆28Updated 4 months ago
• liun-online / SpCo
  The source code of SpCo
  ☆35Updated last year
• zjunet / GPF
  The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.
  ☆28Updated last year
• ChandlerBang / DeCorr
  [KDD 2022] Implementation of "Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective"
  ☆45Updated last year
• CurryTang / TSGFM
  NIPS 24: Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights
  ☆41Updated 2 months ago
• Amanda-Zheng / SFGC
  Pytorch implementation of NeurIPS-23:"Structure-free Graph Condensation (SFGC): From Large-scale Graphs to Condensed Graph-free Data"
  ☆29Updated 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
• 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"
  ☆15Updated last year
• ChandlerBang / GTrans
  [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"
  ☆56Updated last year
• kaize0409 / S-3-CL
  PyTorch Implementation for "Eliciting Structural and Semantic Global Knowledge in Unsupervised Graph Contrastive Learning" (AAAI2023)
  ☆24Updated last month
• yixinliu233 / G-OOD-D
  [WSDM'23] GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection
  ☆38Updated 2 years ago
• THUDM / GRAND-plus
  Code and dataset for paper "GRAND+: Scalable Graph Random Neural Networks"
  ☆33Updated 3 years ago
• yongduosui / AIA
  [NeurIPS 2023] "Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift" by Yongduo Sui, Qitian Wu, Jiancan Wu, Q…
  ☆16Updated last year
• meettyj / NOSMOG
  Code & data for ICLR'23 Spotlight paper "Learning MLPs on Graphs: A Unified View of Effectiveness, Robustness, and Efficiency".
  ☆31Updated 2 years ago
• zyzisastudyreallyhardguy / GOAL-Graph-Complementary-Learning
  The Open Source Code For ICML 2023 Paper "Finding the Missing-half: Graph Complementary Learning for Homophily-prone and Heterophily-pron…
  ☆15Updated last year
• tengxiao1 / Awesome-Graph-Contrastive-Learning-with-Heterophily
  Papers about Graph Contrastive Learning and Graph Self-supervised Learning on Graphs with Heterophily
  ☆36Updated last year
• zhoushengisnoob / CKD
  Code for The Web Conference 2022 Paper "Collaborative Knowledge Distillation for Heterogeneous Information Network Embedding"
  ☆16Updated 3 years ago
• susheels / gnns-and-local-assortativity
  This repo contains a reference implementation for the paper "Breaking the Limit of Graph Neural Networks by Improving the Assortativity o…
  ☆32Updated 3 years ago
• yzjiao / Subg-Con
  Code for ICDM2020 full paper: "Sub-graph Contrast for Scalable Self-Supervised Graph Representation Learning"
  ☆44Updated 3 years ago
• zepengzhang / awesome-graph-structure-learning
  A collection of papers on Graph Structural Learning (GSL)
  ☆54Updated 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…
  ☆32Updated 4 months ago
• Graph-COM / StruRW
  [ICML 2023] Structural Re-weighting Improves Graph Domain Adaptation (StruRW)
  ☆21Updated last year
• Nashchou / MultiGPrompt
  ☆22Updated 5 months ago
• junxia97 / ProGCL
  [ICML 2022] "ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning"
  ☆45Updated 2 years ago