| Human alignment of neural network representations L Muttenthaler, J Dippel, L Linhardt, RA Vandermeulen, S Kornblith International Conference on Learning Representations, 2023 | 38 | 2023 |
| Toward explainable artificial intelligence for precision pathology F Klauschen, J Dippel, P Keyl, P Jurmeister, M Bockmayr, A Mock, ... Annual Review of Pathology: Mechanisms of Disease 19 (1), 541-570, 2024 | 19 | 2024 |
| Improving neural network representations using human similarity judgments L Muttenthaler, L Linhardt, J Dippel, RA Vandermeulen, K Hermann, ... Advances in Neural Information Processing Systems (NeurIPS) 36, 2023 | 19 | 2023 |
| Towards Fine-grained Visual Representations by Combining Contrastive Learning with Image Reconstruction and Attention-weighted Pooling J Dippel, S Vogler, J Höhne ICML Workshop: Self-Supervised Learning for Reasoning and Perception, 2021 | 16 | 2021 |
| Automated data retrieval from large-scale distributed satellite systems D Krupke, V Schaus, A Haas, M Perk, J Dippel, B Grzesik, MKB Larbi, ... 2019 IEEE 15th international conference on automation science and …, 2019 | 12* | 2019 |
| RudolfV: a foundation model by pathologists for pathologists J Dippel, B Feulner, T Winterhoff, S Schallenberg, G Dernbach, A Kunft, ... arXiv preprint arXiv:2401.04079, 2024 | 6 | 2024 |
| Transfer Learning for Segmentation Problems: Choose the Right Encoder and Skip the Decoder J Dippel, M Lenga, T Goerttler, K Obermayer, J Höhne arXiv preprint arXiv:2207.14508, 2022 | 2 | 2022 |
| Erklärbare künstliche intelligenz in der pathologie F Klauschen, J Dippel, P Keyl, P Jurmeister, M Bockmayr, A Mock, ... Forum, 1-7, 2024 | 1 | 2024 |
| AI-based Anomaly Detection for Clinical-Grade Histopathological Diagnostics J Dippel, N Prenißl, J Hense, P Liznerski, T Winterhoff, S Schallenberg, ... arXiv preprint arXiv:2406.14866, 2024 | | 2024 |
| xMIL: Insightful Explanations for Multiple Instance Learning in Histopathology J Hense, MJ Idaji, O Eberle, T Schnake, J Dippel, L Ciernik, O Buchstab, ... arXiv preprint arXiv:2406.04280, 2024 | | 2024 |
| Explainable artificial intelligence in pathology F Klauschen, J Dippel, P Keyl, P Jurmeister, M Bockmayr, A Mock, ... Pathologie (Heidelberg, Germany), 2024 | | 2024 |
| Representation learning J Dippel, S Vogler, J Höhne US Patent App. 18/038,182, 2024 | | 2024 |
Klaus-Robert MüllerGoogle DeepMind & TU Berlin & Korea University & Max Planck Institute for Informatics, GermanyVerified email at tu-berlin.de
