arXiv Machine Learning
Jun 18
Towards Anomaly Detection on Relational Data
arXiv:2606. 18621v1 Announce Type: new Abstract: Relational databases are widely used for managing structured data in real-world systems.
Towards Anomaly Detection on Relational Data
Relational databases are widely used for managing structured data in real-world systems. Detecting anomalies from such relational data is crucial for identifying fraud, risks, and abnormal behaviors, yet remains under-explored.
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arXiv AI
Jun 12
A Zero-shot Generalized Graph Anomaly Detection Framework via Node Reconstruction
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arXiv Machine Learning
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A Survey of Heterogeneous Graph Neural Networks for Cybersecurity Anomaly Detection
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arXiv Machine Learning
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FoundAna: A GNN-assisted Foundation Model for Graph Anomaly Detection
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arXiv AI
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Towards Principled Continual Anomaly Detection: A Systematic Framework and Benchmark Scenarios
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arXiv Machine Learning
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arXiv AI
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Zero-shot Generalizable Graph Anomaly Detection with Mixture of Riemannian Experts
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arXiv AI
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arXiv Machine Learning
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arXiv Machine Learning
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