| Abstracting process mining event logs from process-state data to monitor control-flow of industrial manufacturing processes M Mayr, S Luftensteiner, GC Chasparis Procedia Computer Science 200, 1442-1450, 2022 | 11 | 2022 |
| Filter-based feature selection methods for industrial sensor data: a review S Luftensteiner, M Mayr, G Chasparis International Conference on Big Data Analytics and Knowledge Discovery, 242-249, 2021 | 6 | 2021 |
| Opening the black-box of Neighbor Embeddings with Hotelling’s T2 statistic and Q-residuals RJ Rainer, M Mayr, J Himmelbauer, R Nikzad-Langerodi Chemometrics and Intelligent Laboratory Systems 238, 104840, 2023 | 4 | 2023 |
| Generalized input-output hidden-Markov-models for supervising industrial processes GC Chasparis, S Luftensteiner, M Mayr Procedia Computer Science 200, 1402-1411, 2022 | 4 | 2022 |
| Avubdi: A versatile usable big data infrastructure and its monitoring approaches for process industry S Luftensteiner, M Mayr, GC Chasparis, M Pichler Frontiers in Chemical Engineering 3, 665545, 2021 | 2 | 2021 |
| Gathering Expert Knowledge in Process Industry S Luftensteiner, GC Chasparis, M Mayr Procedia Computer Science 217, 960-968, 2023 | 1 | 2023 |
| From Data to Decisions-Developing Data Analytics Use-Cases in Process Industry J Himmelbauer, M Mayr, S Luftensteiner International Conference on Database and Expert Systems Applications, 79-89, 2022 | | 2022 |
| Detecting Anomalies in Production Quality Data Using a Method Based on the Chi-Square Test Statistic M Mayr, J Himmelbauer International Conference on Big Data Analytics and Knowledge Discovery, 348-363, 2020 | | 2020 |
