Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning (CoLA), TNNLS-21
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Updated
May 12, 2021 - Python
Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning (CoLA), TNNLS-21
Code for Deep Anomaly Detection on Attributed Networks (SDM2019)
[TKDE 2021] A PyTorch implementation of "Generative and Contrastive Self-Supervised Learning for Graph Anomaly Detection".
Implementation of the paper Deep Graph-level Anomaly Detection by Glocal Knowledge Distillation(WSDM22)
A Python Library for Graph Outlier Detection (Anomaly Detection)
The official PyTorch implementation of Cross-Domain Graph Anomaly Detection via Anomaly-aware Contrastive Alignment (AAAI2023, to appear).
Source Code for Paper "DAGAD: Data Augmentation for Graph Anomaly Detection" ICDM 2022
Code for ECMLPKDD23 paper "Graph-level Anomaly Detection via Hierarchical Memory Networks" (HimNet)
Code Repository for Paper "HRGCN: Heterogeneous Graph-level Anomaly Detection with Hierarchical Relation-augmented Graph Neural Networks"
An official source code for paper "ARISE: Graph Anomaly Detection on Attributed Networks via Substructure Awareness", accepted by IEEE TNNLS.
An official source code for paper "Graph Anomaly Detection via Multi-Scale Contrastive Learning Networks with Augmented View", accepted by AAAI 2023.
An official source code for paper "Normality Learning-based Graph Anomaly Detection via Multi-Scale Contrastive Learning", accepted by ACM MM 2023.
The source code of Reinforcement Neighborhood Selection for Unsupervised Graph Anomaly Detection (RAND), ICDM 2023.
Source code for DASFAA'24 paper "Crowdsourcing Fraud Detection over Heterogeneous Temporal MMMA Graph"
Official implementation of NeurIPS'23 paper "Truncated Affinity Maximization: One-class Homophily Modeling for Graph Anomaly Detection"
A Python Library for Graph Outlier Detection (Anomaly Detection)
This code is for paper "Generative Semi-supervised Graph Anomaly Detection"
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