4 papers
JAPE: Joint Anomaly Prediction and Intrinsic Explanation in Multivariate Time Series
Yian Wei, Yuanyuan Yao, Lu Chen +2
Multivariate time-series anomaly prediction aims to identify whether and when anomalies will occur over a future horizon from historical observations. Existing methods primarily ch…
AegisTS: A Hierarchical Agentic AI System with Reinforcement Learning for Multivariate Time Series Data Cleaning
Yuhan Shi, Yuanyuan Yao, Lu Chen +3
Multivariate time series (MTS) are frequently affected by co-occurring quality issues, such as missing values, outliers, and constraint violations, which significantly undermine do…
Moon: A Modality Conversion-based Efficient Multivariate Time Series Anomaly Detection
Yuanyuan Yao, Yuhan Shi, Lu Chen +5
Multivariate time series (MTS) anomaly detection identifies abnormal patterns where each timestamp contains multiple variables. Existing MTS anomaly detection methods fall into thr…
PTST: A polar topological structure toolkit and database
Guanshihan Du, Yuanyuan Yao, Linming Zhou +11
Ferroelectric oxide superlattices with complex topological structures such as vortices, skyrmions, and flux closure domains have garnered significant attention due to their fascina…