| Integration of novel sensors and machine learning for predictive maintenance in medium voltage switchgear to enable the energy and mobility revolutions MW Hoffmann, S Wildermuth, R Gitzel, A Boyaci, J Gebhardt, H Kaul, ... Sensors 20 (7), 2099, 2020 | 56 | 2020 |
| AutoML for Predictive Maintenance: One Tool to RUL them all T Tornede, A Tornede, M Wever, F Mohr, E Hüllermeier IoTStream @ ECMLPKDD 2020, 2020 | 16 | 2020 |
| Coevolution of remaining useful lifetime estimation pipelines for automated predictive maintenance T Tornede, A Tornede, M Wever, E Hüllermeier Proceedings of the genetic and evolutionary computation conference, 368-376, 2021 | 10 | 2021 |
| Towards green automated machine learning: Status quo and future directions T Tornede, A Tornede, J Hanselle, M Wever, F Mohr, E Hüllermeier arXiv preprint arXiv:2111.05850, 2021 | 9 | 2021 |
| Algorithm selection on a meta level A Tornede, L Gehring, T Tornede, M Wever, E Hüllermeier Machine Learning 112 (4), 1253-1286, 2023 | 8 | 2023 |
| jPL: A java-based software framework for preference learning P Gupta, A Hetzer, T Tornede, S Gottschalk, A Kornelsen, S Osterbrink, ... Proceedings of the LWDA, 2017 | 1 | 2017 |
| PyExperimenter: Easily distribute experiments and track results T Tornede, A Tornede, L Fehring, L Gehring, H Graf, J Hanselle, F Mohr, ... arXiv preprint arXiv:2301.06348, 2023 | | 2023 |
| Schlussbericht ITS. ML: Intelligente Technische Systeme der nächsten Generation durch Maschinelles Lernen. Forschungsvorhaben zur automatisierten Analyse von Daten mittels … B Hammer, E Hüllermeier, V Lohweg, A Schneider, W Schenck, U Kuhl, ... | | 2022 |
Eyke HüllermeierProfessor of Computer Science, Paderborn UniversityVerified email at upb.de
