Pinned Repositories
CoLA
[TNNLS] Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning
SUBLIME
[WWW'22] Towards Unsupervised Deep Graph Structure Learning
CoLA
[TNNLS'21] Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning
D2PT
[KDD'23] Learning Strong Graph Neural Networks with Weak Information
FedStar
[AAAI'23] Federated Learning on Non-IID Graphs via Structural Knowledge Sharing
G-OOD-D
[WSDM'23] GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection
GREET
[AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating
SIGNET
[NeurIPS'23] Towards Self-Interpretable Graph-Level Anomaly Detection
SimpDM
[CIKM'24] Self-Supervision Improves Diffusion Models for Tabular Data Imputation
TADDY_pytorch
A Pytorch implement of paper "Anomaly detection in dynamic graphs via transformer" (TADDY).
yixinliu233's Repositories
yixinliu233/GREET
[AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating
yixinliu233/D2PT
[KDD'23] Learning Strong Graph Neural Networks with Weak Information
yixinliu233/G-OOD-D
[WSDM'23] GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection
yixinliu233/SIGNET
[NeurIPS'23] Towards Self-Interpretable Graph-Level Anomaly Detection
yixinliu233/SimpDM
[CIKM'24] Self-Supervision Improves Diffusion Models for Tabular Data Imputation
yixinliu233/TADDY_pytorch
A Pytorch implement of paper "Anomaly detection in dynamic graphs via transformer" (TADDY).
yixinliu233/CoLA
[TNNLS'21] Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning
yixinliu233/SUBLIME
[WWW'22] Towards Unsupervised Deep Graph Structure Learning
yixinliu233/ANEMONE
A PyTorch implementation of "ANEMONE: Graph Anomaly Detection with Multi-Scale Contrastive Learning", CIKM-21
yixinliu233/FedStar
[AAAI'23] Federated Learning on Non-IID Graphs via Structural Knowledge Sharing
yixinliu233/Awesome-Deep-Graph-Anomaly-Detection
Awesome graph anomaly detection techniques built based on deep learning frameworks. Collections of commonly used datasets, papers as well as implementations are listed in this github repository. We also invite researchers interested in anomaly detection, graph representation learning, and graph anomaly detection to join this project as contributors and boost further research in this area.
yixinliu233/SL-GAD
A PyTorch implementation of "Generative and Contrastive Self-Supervised Learning for Graph Anomaly Detection", TKDE-21
yixinliu233/yixinliu233.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes