| Auto-pytorch: Multi-fidelity metalearning for efficient and robust autodl L Zimmer, M Lindauer, F Hutter IEEE transactions on pattern analysis and machine intelligence 43 (9), 3079-3090, 2021 | 236 | 2021 |
| Nas-bench-301 and the case for surrogate benchmarks for neural architecture search J Siems, L Zimmer, A Zela, J Lukasik, M Keuper, F Hutter arXiv preprint arXiv:2008.09777 4, 14, 2020 | 176 | 2020 |
| Surrogate NAS benchmarks: Going beyond the limited search spaces of tabular NAS benchmarks A Zela, J Siems, L Zimmer, J Lukasik, M Keuper, F Hutter arXiv preprint arXiv:2008.09777, 2020 | 66 | 2020 |
| Learn-Morph-Infer: a new way of solving the inverse problem for brain tumor modeling I Ezhov, K Scibilia, K Franitza, F Steinbauer, S Shit, L Zimmer, J Lipkova, ... Medical Image Analysis 83, 102672, 2023 | 15 | 2023 |
| Calibration of intensity spectra from fluorescent nuclear track detectors in clinical ion beams A Verkhovtsev, L Zimmer, S Greilich Radiation Measurements 121, 37-41, 2019 | 6 | 2019 |
| NAS-Bench-301 and the case for surrogate benchmarks for neural architecture search.(2020) J Siems, L Zimmer, A Zela, J Lukasik, M Keuper, F Hutter arXiv preprint arXiv:2008.09777, 2020 | 5 | 2020 |
| Auto-pytorch tabular: Multi-fidelity MetaLearning for efficient and robust AutoDLL. arXiv 2020 L Zimmer, M Lindauer, F Hutter arXiv preprint arXiv:2006.13799, 2000 | 5 | 2000 |
| Towards Image-Based Personalization of Glioblastoma Therapy A Clinical and Biological Validation Study of a Novel, Deep Learning-Driven Tumor Growth Model MC Metz, I Ezhov, L Zimmer, JC Peeken, JA Buchner, J Lipkova, F Kofler, ... | 1 | 2023 |
| Method, device and computer program for predicting a suitable configuration of a machine learning system for a training data set A Zela, F Hutter, J Siems, L Zimmer US Patent App. 16/950,570, 2021 | 1 | 2021 |
| QUBIQ: Uncertainty Quantification for Biomedical Image Segmentation Challenge H Bran, F Navarro, I Ezhov, A Bayat, D Das, F Kofler, S Shit, ... arXiv preprint arXiv:2405.18435, 2024 | | 2024 |
| A for-loop is all you need. For solving the inverse problem in the case of personalized tumor growth modeling I Ezhov, M Rosier, L Zimmer, F Kofler, S Shit, JC Paetzold, K Scibilia, ... Machine Learning for Health, 566-577, 2022 | | 2022 |
| Casting the inverse problem as a database query. The case of personalized tumor growth modeling. I Ezhov, M Rosier, L Zimmer, F Kofler, S Shit, J Paetzold, K Scibilia, ... CoRR, 2022 | | 2022 |
| Schritt in Richtung personalisierter Strahlentherapie MC Metz, L Zimmer, I Ezhov, J Peeken, JA Buchner, B Menze, B Wiestler, ... 57. Jahrestagung der Deutschen Gesellschaft für Neuroradiologie e. V., 71, 0 | | |
