| Towards novel insights in lattice field theory with explainable machine learning S Blücher, L Kades, JM Pawlowski, N Strodthoff, JM Urban Physical Review D 101 (9), 094507, 2020 | 50 | 2020 |
| Reweighting Lefschetz Thimbles S Bluecher, JM Pawlowski, M Scherzer, M Schlosser, IO Stamatescu, ... SciPost Physics 5 (5), 044, 2018 | 26 | 2018 |
| Multi-dimensional concept discovery (MCD): A unifying framework with completeness guarantees J Vielhaben, S Blücher, N Strodthoff Transactions on Machine Learning Research, 2023 | 25 | 2023 |
| PredDiff: Explanations and Interactions from Conditional Expectations S Blücher, J Vielhaben, N Strodthoff Artificial Intelligence 312, 103774, 2022 | 15 | 2022 |
| Decoupling pixel flipping and occlusion strategy for consistent xai benchmarks S Blücher, J Vielhaben, N Strodthoff Transactions on Machine Learning Research, 2024 | 7 | 2024 |
| Sparse subspace clustering for concept discovery (SSCCD) J Vielhaben, S Blücher, N Strodthoff arXiv preprint arXiv:2203.06043, 2022 | 6 | 2022 |
| Reconstructing Kernel-Based Machine Learning Force Fields with Superlinear Convergence S Blücher, KR Müller, S Chmiela Journal of Chemical Theory and Computation 19 (14), 4619-4630, 2023 | 4 | 2023 |
Nils StrodthoffProfessor for eHealth/AI4Health, Oldenburg University, GermanyBestätigte E-Mail-Adresse bei uol.de
