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…
  ☆55Updated 2 years ago
• hengruizhang98 / mvgrl
  DGL Implementation of ICML 2020 Paper 'Contrastive Multi-View Representation Learning on Graphs'
  ☆65Updated last year
• EdisonLeeeee / MaskGAE
  [KDD 2023] What’s Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders
  ☆89Updated 10 months ago
• SitaoLuan / ACM-GNN
  NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…
  ☆85Updated 10 months ago
• TrustAGI-Lab / SUBLIME
  [WWW'22] Towards Unsupervised Deep Graph Structure Learning
  ☆143Updated 2 years ago
• yzjiao / Subg-Con
  Code for ICDM2020 full paper: "Sub-graph Contrast for Scalable Self-Supervised Graph Representation Learning"
  ☆45Updated 3 years ago
• baoyujing / HDMI
  ☆28Updated 4 years ago
• ChandlerBang / SimP-GCN
  Implementation of the WSDM 2021 paper "Node Similarity Preserving Graph Convolutional Networks"
  ☆59Updated 4 years ago
• susheels / adgcl
  Adversarial Graph Augmentation to Improve Graph Contrastive Learning
  ☆89Updated 3 years ago
• yifeiacc / COSTA
  Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning
  ☆49Updated 2 years ago
• BUPT-GAMMA / Graph-Structure-Estimation-Neural-Networks
  Source code for WWW 2021 paper "Graph Structure Estimation Neural Networks"
  ☆58Updated 4 years ago
• SongtaoLiu0823 / LAGNN
  [ICML 2022] Local Augmentation for Graph Neural Networks
  ☆65Updated last year
• Namkyeong / AFGRL
  The official source code for "Augmentation-Free Self-Supervised Learning on Graphs"
  ☆76Updated 3 years ago
• GemsLab / H2GCN
  Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)
  ☆106Updated 3 months ago
• flyingdoog / PTDNet
  Learning to Drop: Robust Graph Neural Network via Topological Denoising & Robust Graph Representation Learning via Neural Sparsification
  ☆81Updated 4 years ago
• yixinliu233 / GREET
  [AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating
  ☆52Updated 2 years ago
• skepsun / Adaptive-Graph-Diffusion-Networks
  ☆49Updated 9 months ago
• bdy9527 / FAGCN
  ☆97Updated 4 years ago
• Namkyeong / BGRL_Pytorch
  Pytorch implementation of "Large-Scale Representation Learning on Graphs via Bootstrapping"
  ☆81Updated 3 years 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
• yanghu819 / Graph-MLP
  ☆77Updated 4 years ago
• hedongxiao-tju / HOG-GCN
  ☆38Updated 3 years ago
• kepsail / SHGP
  NeurIPS 2022 - SHGP
  ☆31Updated 2 years ago
• liangchundong / HGNN-AC
  Source code of "WWW21 - Heterogeneous Graph Neural Network via Attribute Completion"
  ☆35Updated 3 years ago
• junxia97 / SimGRACE
  [WWW 2022] "SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation"
  ☆81Updated 3 years ago
• ChandlerBang / DeCorr
  [KDD 2022] Implementation of "Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective"
  ☆45Updated last year
• hedongxiao-tju / BM-GCN
  The code of paper "Block Modeling-Guided Graph Convolutional Neural Networks".
  ☆33Updated 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
• RecklessRonan / GloGNN
  ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily
  ☆44Updated 3 years ago
• liun-online / HeCo
  The source code of HeCo
  ☆168Updated 3 years ago