Alternatives and similar repositories for WGDN:

Users that are interested in WGDN 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
• hedongxiao-tju / HOG-GCN
  ☆37Updated 3 years ago
• hedongxiao-tju / BM-GCN
  The code of paper "Block Modeling-Guided Graph Convolutional Neural Networks".
  ☆33Updated 3 years ago
• weitianxin / HyperGCL
  [NeurIPS 2022] "Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative" by Tianxin Wei, Yuning You, Tianlong Chen, Y…
  ☆60Updated 2 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
• junxia97 / ProGCL
  [ICML 2022] "ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning"
  ☆45Updated 2 years ago
• ChandlerBang / DeCorr
  [KDD 2022] Implementation of "Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective"
  ☆45Updated last year
• yixinliu233 / G-OOD-D
  [WSDM'23] GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection
  ☆39Updated 2 years ago
• 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
• ZhiningLiu1998 / BAT
  [ICML'24] BAT: 🚀 Boost Class-imbalanced Node Classification with <10 lines of Code | 从拓扑视角出发10行代码改善类别不平衡节点分类
  ☆25Updated 5 months ago
• blacksingular / GHRN
  [WWW 2023] "Addressing Heterophily in Graph Anomaly Detection: A Perspective of Graph Spectrum" by Yuan Gao, Xiang Wang, Xiangnan He, Zhe…
  ☆37Updated last year
• ChandlerBang / AutoSSL
  [ICLR 2022] Implementation of paper "Automated Self-Supervised Learning for Graphs"
  ☆42Updated 2 years ago
• yifeiacc / COSTA
  Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning
  ☆49Updated last year
• LirongWu / GraphMixup
  Code for ECML-PKDD 2022 paper "GraphMixup: Improving Class-Imbalanced Node Classification by Reinforcement Mixup and Self-supervised Cont…
  ☆23Updated last year
• zjunet / GPF
  The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.
  ☆29Updated last year
• YujieMo / DMG
  ☆18Updated last year
• tengxiao1 / GraphACL
  GraphACL: Simple and Asymmetric Graph Contrastive Learning (NeurIPS 2023)
  ☆31Updated 10 months ago
• TrustAGI-Lab / ANEMONE
  [CIKM 2021] A PyTorch implementation of "ANEMONE: Graph Anomaly Detection with Multi-Scale Contrastive Learning".
  ☆49Updated 3 years ago
• RingBDStack / SUGAR
  Code for "SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism"
  ☆57Updated 3 years ago
• zjunet / DropMessage
  The implementation for DropMessage.
  ☆37Updated 2 years ago
• zepengzhang / awesome-graph-structure-learning
  A collection of papers on Graph Structural Learning (GSL)
  ☆54Updated last year
• graphprojects / CM-GCL
  Source code of NeurIPS 2022 paper “Co-Modality Graph Contrastive Learning for Imbalanced Node Classification”
  ☆20Updated 2 years ago
• Graph-COM / GAD-NR
  [WSDM 2024] GAD-NR : Graph Anomaly Detection via Neighborhood Reconstruction
  ☆42Updated 5 months ago
• LirongWu / FF-G2M
  Code for AAAI 2023 (Oral) paper "Extracting Low-/High- Frequency Knowledge from Graph Neural Networks and Injecting it into MLPs: An Effe…
  ☆24Updated 9 months ago
• blacksingular / wsdm_GDN
  [WSDM 2023] "Alleviating Structrual Distribution Shift in Graph Anomaly Detection" by Yuan Gao, Xiang Wang, Xiangnan He, Zhenguang Liu, H…
  ☆21Updated last year
• kepsail / SHGP
  NeurIPS 2022 - SHGP
  ☆31Updated last year
• yuwvandy / DPGNN
  ☆38Updated last year
• SukwonYun / LTE4G
  The official source code for "LTE4G: Long-Tail Experts for Graph Neural Networks" paper, accepted at CIKM 2022.
  ☆39Updated 2 years ago
• qiaoyu-tan / S2GAE
  ☆47Updated 2 years ago