24 citations · 24 across the 8 of their papers we have counts for
4 papers · 1 filter
Exploring Zero-Shot Foundation Models for Multivariate Time Series Anomaly Detection
Martin Uray, Saverio Messineo, Roland Kwitt +1
Multivariate Time Series Anomaly Detection (MTSAD) is essential for reliability and safety in domains such as industrial process monitoring and financial risk management, yet conve…
Anomaly Detection for Sparse and Irregular Multivariate Time Series with Latent SDEs
Martin Uray, Dominik Geng, Florian Graf +2
Multivariate time series anomaly detection (MTSAD) is critical for a wide range of application areas, such as industrial monitoring, cybersecurity, or healthcare. Real-world data i…
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…
Topologically Stable Hough Transform
Stefan Huber, Kristóf Huszár, Michael Kerber +1
We propose an alternative formulation of the well-known Hough transform to detect lines in point clouds. Replacing the discretized voting scheme of the classical Hough transform by…