From the 1 of 5 linked papers with an AI index.
5 papers
Exploring Zero-Shot Foundation Models for Multivariate Time Series Anomaly Detection
Martin Uray, Saverio Messineo, Roland Kwitt +1
The paper investigates using a pre‑trained univariate forecasting foundation model (TimesFM) in a zero‑shot manner for multivariate time‑series anomaly detection on the SWaT benchm…
Federated Learning for Multivariate Time Series Anomaly Detection in Industrial Automation
Khayyam Nosrati, Martin Uray, Saverio Messineo +2
Federated learning (FL) has broadened the horizon for multivariate time series anomaly detection (MTSAD). However, benchmarking such anomaly detection methods within FL paradigm po…
Generative Modeling of Approximately Periodic Time Series by a Posterior-Weighted Gaussian Process
Elias Reich, Saverio Messineo, Stefan Huber
Discrete automated processes in industrial and cyber-physical systems often exhibit a repetitive structure in which successive repetitions follow a common trajectory while differin…
Persistence-based Hough Transform for Line Detection
Johannes Ferner, Stefan Huber, Saverio Messineo +2
The Hough transform is a popular and classical technique in computer vision for the detection of lines (or more general objects). It maps a pixel into a dual space -- the Hough spa…
Topology-driven identification of repetitions in multi-variate time series
Simon Schindler, Elias Steffen Reich, Saverio Messineo +2
Many multi-variate time series obtained in the natural sciences and engineering possess a repetitive behavior, as for instance state-space trajectories of industrial machines in di…