2026
Is Training Necessary for Anomaly Detection?
ICML 2026poster
Current state-of-the-art multi-class unsupervised anomaly detection (MUAD) methods rely on training encoder–decoder models to reconstruct anomaly-free features. We first show these approaches have an inherent fidelity–stability dilemma in how they detect anomalies via reconstruction residuals. We th…