| Layer-wise relevance propagation for explaining deep neural network decisions in MRI-based Alzheimer's disease classification M Böhle, F Eitel, M Weygandt, K Ritter Frontiers in aging neuroscience 11, 194, 2019 | 213 | 2019 |
| Memory-induced acceleration and slowdown of barrier crossing J Kappler, JO Daldrop, FN Brünig, MD Boehle, RR Netz The Journal of Chemical Physics 148 (1), 2018 | 46 | 2018 |
| Convolutional dynamic alignment networks for interpretable classifications M Bohle, M Fritz, B Schiele Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 39 | 2021 |
| B-cos networks: Alignment is all we need for interpretability M Böhle, M Fritz, B Schiele Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 31 | 2022 |
| Towards better understanding attribution methods S Rao, M Böhle, B Schiele Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 21 | 2022 |
| Temperature schedules for self-supervised contrastive methods on long-tail data A Kukleva, M Böhle, B Schiele, H Kuehne, C Rupprecht arXiv preprint arXiv:2303.13664, 2023 | 11 | 2023 |
| Visualizing evidence for Alzheimer’s disease in deep neural networks trained on structural MRI data M Böhle, F Eitel, M Weygandt, K Ritter arXiv preprint arXiv:1903.07317, 2019 | 6 | 2019 |
| Holistically Explainable Vision Transformers M Böhle, M Fritz, B Schiele arXiv preprint arXiv:2301.08669, 2023 | 5 | 2023 |
| Using Explanations to Guide Models S Rao, M Böhle, A Parchami-Araghi, B Schiele arXiv preprint arXiv:2303.11932, 2023 | 2 | 2023 |
| B-cos Alignment for Inherently Interpretable CNNs and Vision Transformers M Böhle, N Singh, M Fritz, B Schiele arXiv preprint arXiv:2306.10898, 2023 | 1 | 2023 |
| Optimising for Interpretability: Convolutional Dynamic Alignment Networks M Böhle, M Fritz, B Schiele IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 | 1 | 2022 |
| Better Understanding Differences in Attribution Methods via Systematic Evaluations S Rao, M Böhle, B Schiele arXiv preprint arXiv:2303.11884, 2023 | | 2023 |
| Studying How to Efficiently and Effectively Guide Models with Explanations S Rao, M Böhle, A Parchami-Araghi, B Schiele Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | | 2023 |
| Towards Better Understanding Attribution Methods Supplementary Material S Rao, M Böhle, B Schiele | | |
Bernt SchieleProfessor, Max Planck Institute for Informatics, Saarland Informatics Campus, Saarland UniversityBestätigte E-Mail-Adresse bei mpi-inf.mpg.de
