Author

James Myles

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Preprint Sep 2026

A Principled Approach to Unsupervised Anomaly Detection

Traditional unsupervised anomaly detection (UAD) methods are designed to flag or localise deviations from a normative distribution, ignoring the underlying generative mechanisms of the anomalies. Yet the nature of an anomaly is often as important as its presence. We reformulate UAD as a Bayesian inverse problem, in whi...

James Myles, Matthew Baugh, J. Müller et al. · 1 citation