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cs.LG2026
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…
cs.LG2026
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…