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Graph Anomaly Detection

Papers

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Showing 1–50 of 87 papers

TitleStatusHype
Temporal-Aware Graph Attention Network for Cryptocurrency Transaction Fraud Detection—0
HLSAD: Hodge Laplacian-based Simplicial Anomaly Detection—0
Chi-Square Wavelet Graph Neural Networks for Heterogeneous Graph Anomaly DetectionCode0
Rethinking Contrastive Learning in Graph Anomaly Detection: A Clean-View Perspective—0
Partition-wise Graph Filtering: A Unified Perspective Through the Lens of Graph CoarseningCode0
EAGLE: Contrastive Learning for Efficient Graph Anomaly Detection—0
Grad: Guided Relation Diffusion Generation for Graph Augmentation in Graph Fraud DetectionCode3
Towards Anomaly-Aware Pre-Training and Fine-Tuning for Graph Anomaly Detection—0
CRC-SGAD: Conformal Risk Control for Supervised Graph Anomaly Detection—0
Unsupervised Graph Anomaly Detection via Multi-Hypersphere Heterophilic Graph LearningCode0
G-OSR: A Comprehensive Benchmark for Graph Open-Set Recognition—0
Graph Anomaly Detection via Adaptive Test-time Representation Learning across Out-of-Distribution Domains—0
AnomalyGFM: Graph Foundation Model for Zero/Few-shot Anomaly DetectionCode1
CurvGAD: Leveraging Curvature for Enhanced Graph Anomaly Detection—0
Out-of-Distribution Detection on Graphs: A SurveyCode1
Semi-supervised Anomaly Detection with Extremely Limited Labels in Dynamic Graphs—0
Towards Automated Self-Supervised Learning for Truly Unsupervised Graph Anomaly DetectionCode0
Bi-directional Curriculum Learning for Graph Anomaly Detection: Dual Focus on Homogeneity and Heterogeneity—0
UMGAD: Unsupervised Multiplex Graph Anomaly Detection—0
UniGAD: Unifying Multi-level Graph Anomaly DetectionCode1
High-Pass Graph Convolutional Network for Enhanced Anomaly Detection: A Novel ApproachCode0
ANOMIX: A Simple yet Effective Hard Negative Generation via Mixing for Graph Anomaly DetectionCode0
Graph Pre-Training Models Are Strong Anomaly Detectors—0
Zero-shot Generalist Graph Anomaly Detection with Unified Neighborhood PromptsCode1
Towards Cross-domain Few-shot Graph Anomaly Detection—0
DiffGAD: A Diffusion-based Unsupervised Graph Anomaly DetectorCode1
Revisiting Multi-Permutation Equivariance through the Lens of Irreducible RepresentationsCode0
PieClam: A Universal Graph Autoencoder Based on Overlapping Inclusive and Exclusive Communities—0
Deep Graph Anomaly Detection: A Survey and New PerspectivesCode3
Towards Multi-view Graph Anomaly Detection with Similarity-Guided Contrastive Clustering—0
A Methodological Report on Anomaly Detection on Dynamic Knowledge Graphs—0
Online Detection of Anomalies in Temporal Knowledge Graphs with InterpretabilityCode0
Graph Anomaly Detection with Noisy Labels by Reinforcement Learning—0
Counterfactual Data Augmentation with Denoising Diffusion for Graph Anomaly DetectionCode0
Enhancing Fairness in Unsupervised Graph Anomaly Detection through DisentanglementCode0
ARC: A Generalist Graph Anomaly Detector with In-Context LearningCode1
Guarding Graph Neural Networks for Unsupervised Graph Anomaly Detection—0
Polynomial Selection in Spectral Graph Neural Networks: An Error-Sum of Function Slices ApproachCode0
Temporal Graph Networks for Graph Anomaly Detection in Financial Networks—0
Generation is better than Modification: Combating High Class Homophily Variance in Graph Anomaly Detection—0
Three Revisits to Node-Level Graph Anomaly Detection: Outliers, Message Passing and Hyperbolic Neural NetworksCode0
Towards Fair Graph Anomaly Detection: Problem, Benchmark Datasets, and EvaluationCode1
FGAD: Self-boosted Knowledge Distillation for An Effective Federated Graph Anomaly Detection Framework—0
Generative Semi-supervised Graph Anomaly DetectionCode2
Alleviating Structural Distribution Shift in Graph Anomaly DetectionCode1
Multitask Active Learning for Graph Anomaly DetectionCode0
ADA-GAD: Anomaly-Denoised Autoencoders for Graph Anomaly DetectionCode1
Reinforcement Neighborhood Selection for Unsupervised Graph Anomaly Detection—0
Few-shot Message-Enhanced Contrastive Learning for Graph Anomaly Detection—0
Open-Set Graph Anomaly Detection via Normal Structure Regularisation—0
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