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cs.LG2023
Prototypes as Explanation for Time Series Anomaly Detection
Bin Li, Carsten Jentsch, Emmanuel Müller
Detecting abnormal patterns that deviate from a certain regular repeating pattern in time series is essential in many big data applications. However, the lack of labels, the dynami…
cs.LG2020
Differentiable Segmentation of Sequences
Erik Scharwächter, Jonathan Lennartz, Emmanuel Müller
Segmented models are widely used to describe non-stationary sequential data with discrete change points. Their estimation usually requires solving a mixed discrete-continuous optim…
cs.LG2019
Deep Semi-Supervised Anomaly Detection
Lukas Ruff, Robert A. Vandermeulen, Nico Görnitz +4
Deep approaches to anomaly detection have recently shown promising results over shallow methods on large and complex datasets. Typically anomaly detection is treated as an unsuperv…