Alternatives and similar repositories for S2GAE

Users that are interested in S2GAE are comparing it to the libraries listed below

• FelixDJC / GRADATE
  An official source code for paper "Graph Anomaly Detection via Multi-Scale Contrastive Learning Networks with Augmented View", accepted b…
  ☆62Updated last year
• TrustAGI-Lab / SUBLIME
  [WWW'22] Towards Unsupervised Deep Graph Structure Learning
  ☆142Updated 2 years ago
• SitaoLuan / ACM-GNN
  NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…
  ☆84Updated 8 months ago
• yixinliu233 / D2PT
  [KDD'23] Learning Strong Graph Neural Networks with Weak Information
  ☆42Updated 2 years ago
• snap-research / linkless-link-prediction
  [ICML 2023] Linkless Link Prediction via Relational Distillation
  ☆23Updated last year
• wenzhilics / GraphSHA
  "GraphSHA: Synthesizing Harder Samples for Class-Imbalanced Node Classification" in KDD'23
  ☆30Updated last year
• squareRoot3 / GADBench
  "GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection" in NeurIPS 2023
  ☆129Updated last year
• KellyGong / SparseGAD
  ☆18Updated 2 years ago
• SongtaoLiu0823 / LAGNN
  [ICML 2022] Local Augmentation for Graph Neural Networks
  ☆65Updated last year
• BUPT-GAMMA / GCIL
  Code for AAAI-2024 paper: Graph Contrastive Invariant Learning from the Causal Perspective
  ☆26Updated last year
• zepengzhang / awesome-graph-structure-learning
  A collection of papers on Graph Structural Learning (GSL)
  ☆55Updated last year
• yixinliu233 / GREET
  [AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating
  ☆52Updated 2 years ago
• TrustAGI-Lab / CoLA
  [TNNLS] Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning
  ☆94Updated 4 years ago
• SitaoLuan / When-Do-GNNs-Help
  Official repository for NeurIPS 2023 paper "When Do Graph Neural Networks Help with Node Classification? Investigating the Impact of Homo…
  ☆21Updated 8 months ago
• YujieMo / SUGRL
  ☆47Updated 2 years ago
• gongchenghua / Papers-Graphs-with-Heterophily
  A Survey of Learning from Graphs with Heterophily
  ☆145Updated 5 months ago
• zjunet / AMNet
  ☆38Updated 3 years ago
• junxia97 / SimGRACE
  [WWW 2022] "SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation"
  ☆81Updated 3 years ago
• 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
• ahxt / g-mixup
  [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification
  ☆106Updated last year
• UB-GOLD / UB-GOLD
  ICLR25_Unifying Unsupervised Graph-Level Out-of-Distribution Detection and Anomaly Detection: A Benchmark
  ☆58Updated 10 months ago
• yixinliu233 / G-OOD-D
  [WSDM'23] GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection
  ☆43Updated 2 years ago
• hedongxiao-tju / HOG-GCN
  ☆38Updated 3 years ago
• TrustAGI-Lab / ANEMONE
  [CIKM 2021] A PyTorch implementation of "ANEMONE: Graph Anomaly Detection with Multi-Scale Contrastive Learning".
  ☆49Updated 3 years ago
• LUMIA-Group / OrderedGNN
  The official implementation of the paper "Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing" (ICLR 2023).
  ☆46Updated last year
• alexfanjn / FAGCN_PyG
  Reimplementation of AAAI21 paper "Beyond Low-frequency Information in Graph Convolutional Networks" based on PyTorch and PyTorch Geometri…
  ☆23Updated 2 years ago
• bdy9527 / FAGCN
  ☆97Updated 4 years ago
• RecklessRonan / GloGNN
  ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily
  ☆44Updated 3 years ago
• zjunet / DropMessage
  The implementation for DropMessage.
  ☆37Updated 2 years ago
• graph-level-anomalies / iGAD
  ☆12Updated 2 years ago