Alternatives and similar repositories for DGLD

Users that are interested in DGLD 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…
  ☆56Updated 2 years ago
• MingChen-Sun / GPPT
  ☆62Updated 3 years ago
• TrustAGI-Lab / SUBLIME
  [WWW'22] Towards Unsupervised Deep Graph Structure Learning
  ☆143Updated 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 3 years ago
• Xtra-Computing / Awesome-Literature-ILoGs
  Awesome literature on imbalanced learning on graphs
  ☆74Updated last year
• kepsail / SHGP
  NeurIPS 2022 - SHGP
  ☆32Updated 2 years ago
• kaize0409 / awesome-graph-data-augmentaion
  A curated list of publications and code about data augmentaion for graphs.
  ☆63Updated 3 years ago
• Orion-wyc / GAGA
  Fraud Detection, Low Homophily, Label Utilization, Graph Mining
  ☆52Updated 2 years ago
• blacksingular / GHRN
  [WWW 2023] "Addressing Heterophily in Graph Anomaly Detection: A Perspective of Graph Spectrum" by Yuan Gao, Xiang Wang, Xiangnan He, Zhe…
  ☆39Updated 2 years ago
• THUDM / GraphCAD
  TKDE'22-GraphCAD: https://arxiv.org/pdf/2108.07516.pdf
  ☆33Updated 3 years ago
• junxia97 / ProGCL
  [ICML 2022] "ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning"
  ☆46Updated 3 years ago
• TrustAGI-Lab / ANEMONE
  [CIKM 2021] A PyTorch implementation of "ANEMONE: Graph Anomaly Detection with Multi-Scale Contrastive Learning".
  ☆49Updated 4 years ago
• yifeiacc / COSTA
  Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning
  ☆49Updated 2 years ago
• YujieMo / SUGRL
  ☆47Updated 3 years ago
• FraudDetection / FRAUDRE
  ☆37Updated 3 years ago
• squareRoot3 / Rethinking-Anomaly-Detection
  "Rethinking Graph Neural Networks for Anomaly Detection" in ICML 2022
  ☆195Updated last year
• Starlien95 / GraphPrompt
  GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks
  ☆163Updated last year
• junxia97 / SimGRACE
  [WWW 2022] "SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation"
  ☆81Updated 3 years ago
• zjunet / AMNet
  ☆38Updated 3 years ago
• zhiming-xu / conad
  Contrastive Attributed Network Anomaly Detection with Data Augmentation (PAKDD'22)
  ☆28Updated 3 years ago
• ahxt / g-mixup
  [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification
  ☆105Updated last year
• zaixizhang / Graph_Transformer
  A pytorch implementation of graph transformer for node classification
  ☆33Updated 2 years ago
• liun-online / HeCo
  The source code of HeCo
  ☆170Updated 3 years ago
• zhao-tong / Graph-Anomaly-Loss
  TNNLS: A Synergistic Approach for Graph Anomaly Detection with Pattern Mining and Feature Learning; CIKM'20: Error-bounded Graph Anomaly …
  ☆43Updated 2 years ago
• ChandlerBang / GTrans
  [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"
  ☆65Updated 2 years ago
• victorchen96 / ReNode
  Code for Neurips2021 Paper "Topology-Imbalance Learning for Semi-Supervised Node Classification".
  ☆56Updated 4 years ago
• qiaoyu-tan / S2GAE
  ☆49Updated 2 years ago
• THUMNLab / awesome-graph-ood
  Papers about out-of-distribution generalization on graphs.
  ☆168Updated 2 years ago
• EdisonLeeeee / GraphData
  A collection of graph data used for semi-supervised node classification.
  ☆40Updated 3 years ago
• CurryTang / LLMGNN
  Label-free Node Classification on Graphs with Large Language Models (LLMS)
  ☆91Updated 2 years ago