JAPE: Joint Anomaly Prediction and Intrinsic Explanation in Multivariate Time Series

Excerpt

arXiv:2608.11801v2 Announce Type: replace Abstract: Multivariate time-series anomaly prediction aims to identify whether and when anomalies will occur over a future horizon from historical observations. Existing methods primarily characterize anomalies as deviations in future numerical values, which may overlook subtle dependency changes induced by weak anomaly precursors and provide no native variable-level explanation together with the alert. To bridge these gaps, we propose JAPE, a Joint Anom