20 citations · 88 across the 22 of their papers we have counts for
9 papers · 1 filter
Federated Learning for Autoencoder-based Condition Monitoring in the Industrial Internet of Things
Soeren Becker, Kevin Styp-Rekowski, Oliver Vincent Leon Stoll +1
Enabled by the increasing availability of sensor data monitored from production machinery, condition monitoring and predictive maintenance methods are key pillars for an efficient…
A2Log: Attentive Augmented Log Anomaly Detection
Thorsten Wittkopp, Alexander Acker, Sasho Nedelkoski +4
Anomaly detection becomes increasingly important for the dependability and serviceability of IT services. As log lines record events during the execution of IT services, they are a…
Autoencoder-based Condition Monitoring and Anomaly Detection Method for Rotating Machines
Sabtain Ahmad, Kevin Styp-Rekowski, Sasho Nedelkoski +1
Rotating machines like engines, pumps, or turbines are ubiquitous in modern day societies. Their mechanical parts such as electrical engines, rotors, or bearings are the major comp…
Optimizing Convergence for Iterative Learning of ARIMA for Stationary Time Series
Kevin Styp-Rekowski, Florian Schmidt, Odej Kao
Forecasting of time series in continuous systems becomes an increasingly relevant task due to recent developments in IoT and 5G. The popular forecasting model ARIMA is applied to a…
Artificial Intelligence for IT Operations (AIOPS) Workshop White Paper
Jasmin Bogatinovski, Sasho Nedelkoski, Alexander Acker +5
Artificial Intelligence for IT Operations (AIOps) is an emerging interdisciplinary field arising in the intersection between the research areas of machine learning, big data, strea…
Learning more expressive joint distributions in multimodal variational methods
Sasho Nedelkoski, Mihail Bogojeski, Odej Kao
Data often are formed of multiple modalities, which jointly describe the observed phenomena. Modeling the joint distribution of multimodal data requires larger expressive power to…