| Explanations can be manipulated and geometry is to blame AK Dombrowski, M Alber, C Anders, M Ackermann, KR Müller, P Kessel Advances in neural information processing systems 32, 2019 | 370 | 2019 |
| Interpreting and explaining deep neural networks for classification of audio signals S Becker, M Ackermann, S Lapuschkin, KR Müller, W Samek arXiv preprint arXiv:1807.03418 1, 2018 | 236 | 2018 |
| Interpreting and explaining deep neural networks for classification of audio signals. arXiv 2018 S Becker, M Ackermann, S Lapuschkin, KR Müller, W Samek arXiv preprint arXiv:1807.03418, 1807 | 10 | 1807 |
| NFDI4DS Infrastructure and Services S Schimmler, B Wentzel, A Bleier, S Dietze, S Karmakar, P Mutschke, ... Gesellschaft für Informatik eV, 2023 | 2 | 2023 |
| No Shifted Augmentations (NSA): compact distributions for robust self-supervised Anomaly Detection M Yousef, M Ackermann, U Kurup, T Bishop Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2023 | 2 | 2023 |
| Automated graph-based identification of early adopter users G Zappella, M Ackermann, R Jenatton, DS Palfrey, ST Sandler US Patent 10,049,375, 2018 | 2 | 2018 |
| Research Knowledge Graphs in NFDI4DS S Karmakar, M Zloch, F Limani, B Zapilko, S Upadhyaya, J D’Souza, ... Gesellschaft für Informatik eV, 2023 | | 2023 |
| Automated graph-based identification of early adopter users G Zappella, M Ackermann, R Jenatton, DS Palfrey, ST Sandler US Patent App. 10/049,375, 2018 | | 2018 |
| Distant Supervised Relation Extraction. M Ackermann Informatiktage, 39-42, 2012 | | 2012 |
| Distant Supervised Relation Extraction with Wikipedia and Freebase M Ackermann | | |
| Toward Successful Participation in Machine Learning Contests M Ackermann, C Dann, T Plötz | | |
Klaus-Robert MüllerGoogle DeepMind & TU Berlin & Korea University & Max Planck Institute for Informatics, GermanyVerified email at tu-berlin.de
