From attribution maps to human-understandable explanations through concept relevance propagation R Achtibat, M Dreyer, I Eisenbraun, S Bosse, T Wiegand, W Samek, ... Nature Machine Intelligence 5 (9), 1006-1019, 2023 | 162* | 2023 |
Towards trustworthy AI in dentistry J Ma, L Schneider, S Lapuschkin, R Achtibat, M Duchrau, J Krois, ... Journal of Dental Research 101 (11), 1263-1268, 2022 | 52 | 2022 |
Revealing hidden context bias in segmentation and object detection through concept-specific explanations M Dreyer, R Achtibat, T Wiegand, W Samek, S Lapuschkin Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 26* | 2023 |
AttnLRP: Attention-aware Layer-wise Relevance Propagation for Transformers R Achtibat, SMV Hatefi, M Dreyer, A Jain, T Wiegand, S Lapuschkin, ... arXiv preprint arXiv:2402.05602, 2024 | 20 | 2024 |
Understanding the (extra-) ordinary: Validating deep model decisions with prototypical concept-based explanations M Dreyer, R Achtibat, W Samek, S Lapuschkin Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 12 | 2024 |
Pruning by explaining revisited: Optimizing attribution methods to prune cnns and transformers SMV Hatefi, M Dreyer, R Achtibat, T Wiegand, W Samek, S Lapuschkin arXiv preprint arXiv:2408.12568, 2024 | 2 | 2024 |
Explainable concept mappings of MRI: Revealing the mechanisms underlying deep learning-based brain disease classification C Tinauer, A Damulina, M Sackl, M Soellradl, R Achtibat, M Dreyer, ... World Conference on Explainable Artificial Intelligence, 202-216, 2024 | 1 | 2024 |
Pruning By Explaining Revisited: Optimizing Attribution Methods to Prune CNNs and Transformers SM Vakilzadeh Hatefi, M Dreyer, R Achtibat, T Wiegand, W Samek, ... arXiv e-prints, arXiv: 2408.12568, 2024 | | 2024 |
Alle Internetquellen wurden zuletzt am 10. Juli 2024 abgerufen. D Acemoglu, A Ozdaglar, A Tahbaz-Salehi, R Achtibat, M Dreyer, ... | | |