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Graph Anomaly Detection

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/ChunjingXiao/CAGAD

공식 코드

Counterfactual Data Augmentation with Denoising Diffusion for Graph Anomaly Detection

https://github.com/IsolationKernel/Codes

공식 코드

Subgraph Centralization: A Necessary Step for Graph Anomaly Detection

https://github.com/Juintin/GAE-AT

공식 코드

On Generalization of Graph Autoencoders with Adversarial Training

https://github.com/Lemon-cmd/energy-transformer-graph

공식 코드

Energy Transformer

https://github.com/Lemon-cmd/energy-transformer-torch

공식 코드

Energy Transformer

https://github.com/WangXuhongCN/OCGNN

공식 코드

One-Class Graph Neural Networks for Anomaly Detection in Attributed Networks

https://github.com/XiaoxiaoMa-MQ/Awesome-Deep-Graph-Anomaly-Detection

공식 코드

A Comprehensive Survey on Graph Anomaly Detection with Deep Learning

https://github.com/YangSJ2019/AHEAD

공식 코드

AHEAD: A Triple Attention Based Heterogeneous Graph Anomaly Detection Approach

https://github.com/ahachang/defend

공식 코드

Enhancing Fairness in Unsupervised Graph Anomaly Detection through Disentanglement

https://github.com/ahachang/mitigate

공식 코드

Multitask Active Learning for Graph Anomaly Detection

https://github.com/bhoov/energy-transformer-jax

공식 코드

Energy Transformer

https://github.com/blacksingular/wsdm_gdn

공식 코드

Alleviating Structural Distribution Shift in Graph Anomaly Detection

https://github.com/ca1man-2022/awesome-good-detection

공식 코드

Out-of-Distribution Detection on Graphs: A Survey

https://github.com/campanulabells/prem-gad

공식 코드

PREM: A Simple Yet Effective Approach for Node-Level Graph Anomaly Detection

https://github.com/dm2-nd/eland

공식 코드

Action Sequence Augmentation for Early Graph-based Anomaly Detection

https://github.com/fanzhenliu/dagad

공식 코드

DAGAD: Data Augmentation for Graph Anomaly Detection

https://github.com/felixdjc/nlgad

공식 코드

Normality Learning-based Graph Anomaly Detection via Multi-Scale Contrastive Learning

https://github.com/fortunato-all/LJH_DiffGAD

공식 코드

DiffGAD: A Diffusion-based Unsupervised Graph Anomaly Detector

https://github.com/graph-com/gad-nr

공식 코드

GAD-NR: Graph Anomaly Detection via Neighborhood Reconstruction

https://github.com/hsipingli/chigad

공식 코드

Chi-Square Wavelet Graph Neural Networks for Heterogeneous Graph Anomaly Detection

https://github.com/jhkim611/clad

공식 코드

Class Label-aware Graph Anomaly Detection

https://github.com/jing-ds/hnn_gad

공식 코드

Three Revisits to Node-Level Graph Anomaly Detection: Outliers, Message Passing and Hyperbolic Neural Networks

https://github.com/jweihe/ADA-GAD

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ADA-GAD: Anomaly-Denoised Autoencoders for Graph Anomaly Detection

https://github.com/kdegroup/cmt

공식 코드

Crowdsourcing Fraud Detection over Heterogeneous Temporal MMMA Graph

https://github.com/kennynh/mhetgl

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Unsupervised Graph Anomaly Detection via Multi-Hypersphere Heterophilic Graph Learning

https://github.com/lingxiaoshawn/glam

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Graph Anomaly Detection with Unsupervised GNNs

https://github.com/lllyyq1121/unigad

공식 코드

UniGAD: Unifying Multi-level Graph Anomaly Detection

https://github.com/mala-lab/UNPrompt

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Zero-shot Generalist Graph Anomaly Detection with Unified Neighborhood Prompts

https://github.com/mala-lab/anomalygfm

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AnomalyGFM: Graph Foundation Model for Zero/Few-shot Anomaly Detection

https://github.com/mala-lab/awesome-deep-graph-anomaly-detection

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Deep Graph Anomaly Detection: A Survey and New Perspectives

https://github.com/mala-lab/ggad

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Generative Semi-supervised Graph Anomaly Detection

https://github.com/mala-lab/tam-master

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Truncated Affinity Maximization: One-class Homophily Modeling for Graph Anomaly Detection

https://github.com/meteor0033/high-pass_gad

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High-Pass Graph Convolutional Network for Enhanced Anomaly Detection: A Novel Approach

https://github.com/missinghwan/MSAD

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Label-based Graph Augmentation with Metapath for Graph Anomaly Detection

https://github.com/missinghwan/anomix

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ANOMIX: A Simple yet Effective Hard Negative Generation via Mixing for Graph Anomaly Detection

https://github.com/missinghwan/mgad

공식 코드

Label-based Graph Augmentation with Metapath for Graph Anomaly Detection

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.