Explainable deep one-class classification P Liznerski, L Ruff, RA Vandermeulen, BJ Franks, M Kloft, KR Müller arXiv preprint arXiv:2007.01760, 2020 | 238 | 2020 |
Rethinking assumptions in deep anomaly detection L Ruff, RA Vandermeulen, BJ Franks, KR Müller, M Kloft arXiv preprint arXiv:2006.00339, 2020 | 97 | 2020 |
Exposing outlier exposure: What can be learned from few, one, and zero outlier images P Liznerski, L Ruff, RA Vandermeulen, BJ Franks, KR Müller, M Kloft arXiv preprint arXiv:2205.11474, 2022 | 34 | 2022 |
Explainable deep one-class classification. arXiv 2020 P Liznerski, L Ruff, RA Vandermeulen, BJ Franks, M Kloft, KR Müller arXiv preprint arXiv:2007.01760, 0 | 8 | |
Deep anomaly detection on Tennessee Eastman process data F Hartung, BJ Franks, T Michels, D Wagner, P Liznerski, S Reithermann, ... Chemie Ingenieur Technik 95 (7), 1077-1082, 2023 | 7 | 2023 |
Rethinking assumptions in deep anomaly detection. arXiv 2020 L Ruff, RA Vandermeulen, BJ Franks, KR Müller, M Kloft arXiv preprint arXiv:2006.00339, 0 | 6 | |
Weisfeiler-Leman at the margin: When more expressivity matters BJ Franks, C Morris, A Velingker, F Geerts arXiv preprint arXiv:2402.07568, 2024 | 4 | 2024 |
Ordinal regression for difficulty prediction of StepMania levels BJ Franks, B Dinkelmann, M Kloft, S Fellenz Joint European Conference on Machine Learning and Knowledge Discovery in …, 2023 | 1 | 2023 |
Ordinal Regression for Difficulty Estimation of StepMania Levels BJ Franks, B Dinkelmann, S Fellenz, M Kloft arXiv preprint arXiv:2301.09485, 2023 | 1 | 2023 |
A systematic approach to universal random features in graph neural networks BJ Franks, M Anders, M Kloft, P Schweitzer Transactions on Machine Learning Research, 2023 | 1 | 2023 |
A systematic approach to random data augmentation on graph neural networks BJ Franks, M Anders, M Kloft, P Schweitzer arXiv preprint arXiv:2112.04314, 2021 | | 2021 |