2 papers
cs.LG2025
Autoencoders for Anomaly Detection are Unreliable
Roel Bouman, Tom Heskes
Autoencoders are frequently used for anomaly detection, both in the unsupervised and semi-supervised settings. They rely on the assumption that when trained using the reconstructio…
cs.LG2024
Acquiring Better Load Estimates by Combining Anomaly and Change Point Detection in Power Grid Time-series Measurements
Roel Bouman, Linda Schmeitz, Luco Buise +3
In this paper we present novel methodology for automatic anomaly and switch event filtering to improve load estimation in power grid systems. By leveraging unsupervised methods wit…