2 papers
stat.ML2026
Early Failure Prediction from Near-Anomaly Detection: A Proactive Approach
L{é}a Billet, Louise Trav{é}-Massuy{è}s, Elodie Chanthery +1
Anomaly detection methods often have uncertain behavior with respect to samples near the distribution boundary, limiting their ability to anticipate future anomalies. This work int…
cs.LG2026
CLOE: Christoffel Loss Autoencoder for Anomaly Detection
Léa Billet, Louise Travé-Massuyès, Elodie Chanthery +1
Semi-supervised anomaly detection plays a key role in diverse fields such as process monitoring, healthcare, and finance. However, lightweight methods often struggle with high-dime…