Alternatives and similar repositories for RoSA

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

• zyzisastudyreallyhardguy / Graph-Group-Discrimination
  Code for NeurIPS 2022 paper "Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discriminat…
  ☆55Updated 2 years ago
• yixinliu233 / GREET
  [AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating
  ☆52Updated 2 years ago
• yixinliu233 / G-OOD-D
  [WSDM'23] GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection
  ☆43Updated 2 years ago
• RecklessRonan / GloGNN
  ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily
  ☆44Updated 3 years ago
• yifeiacc / COSTA
  Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning
  ☆49Updated 2 years ago
• jumxglhf / ParetoGNN
  Official repository for ICLR'23 paper: Multi-task Self-supervised Graph Neural Network Enable Stronger Task Generalization
  ☆39Updated 2 years ago
• ChandlerBang / DeCorr
  [KDD 2022] Implementation of "Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective"
  ☆45Updated last year
• Namkyeong / BGRL_Pytorch
  Pytorch implementation of "Large-Scale Representation Learning on Graphs via Bootstrapping"
  ☆81Updated 3 years ago
• EnyanDai / NRGNN
  Offical pytorch implementation of proposed NRGNN and Compared Methods in "NRGNN: Learning a Label Noise-Resistant Graph Neural Network on…
  ☆43Updated 3 years ago
• BUPT-GAMMA / Graph-Structure-Estimation-Neural-Networks
  Source code for WWW 2021 paper "Graph Structure Estimation Neural Networks"
  ☆58Updated 4 years ago
• Namkyeong / AFGRL
  The official source code for "Augmentation-Free Self-Supervised Learning on Graphs"
  ☆76Updated 3 years ago
• hengruizhang98 / CCA-SSG
  Codes for 'From Canonical Correlation Analysis to Self-supervised Graph Neural Networks'. https://arxiv.org/abs/2106.12484
  ☆69Updated last year
• lsh0520 / RGCL
  Ratioanle-aware Graph Contrastive Learning codebase
  ☆44Updated 2 years ago
• junxia97 / ProGCL
  [ICML 2022] "ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning"
  ☆45Updated 3 years ago
• RingBDStack / VIB-GSL
  Code for "Graph Structure Learning with Variational Information Bottleneck" published in AAAI 2022
  ☆37Updated 3 years ago
• susheels / adgcl
  Adversarial Graph Augmentation to Improve Graph Contrastive Learning
  ☆89Updated 3 years ago
• hengruizhang98 / mvgrl
  DGL Implementation of ICML 2020 Paper 'Contrastive Multi-View Representation Learning on Graphs'
  ☆65Updated last year
• yixinliu233 / D2PT
  [KDD'23] Learning Strong Graph Neural Networks with Weak Information
  ☆42Updated 2 years ago
• ChandlerBang / GTrans
  [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"
  ☆61Updated 2 years ago
• GemsLab / CPGNN
  ☆29Updated 3 years ago
• baoyujing / HDMI
  ☆28Updated 4 years ago
• junxia97 / SimGRACE
  [WWW 2022] "SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation"
  ☆81Updated 3 years ago
• kepsail / SHGP
  NeurIPS 2022 - SHGP
  ☆31Updated 2 years ago
• CurvCluster / Congregate
  ☆11Updated 2 years ago
• LirongWu / Homophily-Enhanced-Self-supervision
  Code for TNNLS paper "Homophily-Enhanced Self-supervision for Graph Structure Learning: Insights and Directions"
  ☆15Updated last year
• Xzh0u / GBK-GNN
  Code for GBK-GNN (paper accepted by WWW2022)
  ☆16Updated 3 years ago
• SukwonYun / LTE4G
  [CIKM 2023] Code for the paper "LTE4G: Long-Tail Experts for Graph Neural Networks"
  ☆40Updated 3 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
• kaize0409 / S-3-CL
  PyTorch Implementation for "Eliciting Structural and Semantic Global Knowledge in Unsupervised Graph Contrastive Learning" (AAAI2023)
  ☆25Updated 7 months ago
• 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