Alternatives and similar repositories for n2n:

Users that are interested in n2n 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…
  ☆54Updated last year
• GemsLab / CPGNN
  ☆28Updated 3 years ago
• ChandlerBang / DeCorr
  [KDD 2022] Implementation of "Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective"
  ☆45Updated last year
• 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
• Namkyeong / BGRL_Pytorch
  Pytorch implementation of "Large-Scale Representation Learning on Graphs via Bootstrapping"
  ☆78Updated 3 years ago
• kepsail / SHGP
  NeurIPS 2022 - SHGP
  ☆30Updated last year
• ChandlerBang / SimP-GCN
  Implementation of the WSDM 2021 paper "Node Similarity Preserving Graph Convolutional Networks"
  ☆60Updated 3 years ago
• RingBDStack / SUGAR
  Code for "SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism"
  ☆54Updated 3 years ago
• yixinliu233 / GREET
  [AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating
  ☆49Updated 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
• 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
• meettyj / NOSMOG
  Code & data for ICLR'23 Spotlight paper "Learning MLPs on Graphs: A Unified View of Effectiveness, Robustness, and Efficiency".
  ☆31Updated last year
• jindi-tju / U-GCN
  Source code of "NeurIPS21 - Universal Graph Convolutional Networks"
  ☆20Updated 3 years ago
• LirongWu / Homophily-Enhanced-Self-supervision
  Code for TNNLS paper "Homophily-Enhanced Self-supervision for Graph Structure Learning: Insights and Directions"
  ☆14Updated 11 months ago
• RecklessRonan / GloGNN
  ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily
  ☆42Updated 2 years ago
• yifeiacc / COSTA
  Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning
  ☆48Updated last year
• THUDM / GRAND-plus
  Code and dataset for paper "GRAND+: Scalable Graph Random Neural Networks"
  ☆32Updated 2 years ago
• EdisonLeeeee / MaskGAE
  [KDD 2023] What’s Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders
  ☆82Updated 3 months ago
• weitianxin / HyperGCL
  [NeurIPS 2022] "Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative" by Tianxin Wei, Yuning You, Tianlong Chen, Y…
  ☆54Updated 2 years ago
• Xzh0u / GBK-GNN
  Code for GBK-GNN (paper accepted by WWW2022)
  ☆15Updated 2 years ago
• SongtaoLiu0823 / LAGNN
  [ICML 2022] Local Augmentation for Graph Neural Networks
  ☆66Updated 7 months ago
• EnyanDai / RSGNN
  An official PyTorch implementation of "Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels" (WSDM 2022))
  ☆32Updated 2 years ago
• AndyJZhao / WSDM23-GSR
  ☆18Updated last year
• junxia97 / ProGCL
  [ICML 2022] "ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning"
  ☆45Updated 2 years ago
• liun-online / CoGSL
  Official Code: TheWebConf 2022 Compact Graph Structure Learning via Mutual Information Compression
  ☆24Updated 10 months ago
• yzjiao / Subg-Con
  Code for ICDM2020 full paper: "Sub-graph Contrast for Scalable Self-Supervised Graph Representation Learning"
  ☆44Updated 2 years ago
• BorealisAI / SLAPS-GNN
  PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"
  ☆87Updated 3 years ago
• ChandlerBang / AutoSSL
  [ICLR 2022] Implementation of paper "Automated Self-Supervised Learning for Graphs"
  ☆41Updated 2 years ago
• jcheng66 / WGDN
  Wiener Graph Deconvolutional Network Improves Self-Supervised Learning in AAAI 2023
  ☆18Updated 9 months ago
• hedongxiao-tju / BM-GCN
  The code of paper "Block Modeling-Guided Graph Convolutional Neural Networks".
  ☆31Updated 3 years ago