Showing cs.LGShow all
2 papers · 1 filter
cs.LG2026
Strong Linear Baselines Strike Back: Closed-Form Linear Models as Gaussian Process Conditional Density Estimators for TSAD
Aleksandr Yugay, Hang Cui, Changhua Pei +1
Research in time series anomaly detection (TSAD) has largely focused on developing increasingly sophisticated, hard-to-train, and expensive-to-infer neural architectures. We revisi…
cs.LG2025
ViTs: Teaching Machines to See Time Series Anomalies Like Human Experts
Zexin Wang, Changhua Pei, Yang Liu +8
Web service administrators must ensure the stability of multiple systems by promptly detecting anomalies in Key Performance Indicators (KPIs). Achieving the goal of "train once, in…