| Meta-learning acquisition functions for transfer learning in bayesian optimization M Volpp, LP Fröhlich, K Fischer, A Doerr, S Falkner, F Hutter, C Daniel arXiv preprint arXiv:1904.02642, 2019 | 96 | 2019 |
| Decomposing neural networks as mappings of correlation functions K Fischer, A René, C Keup, M Layer, D Dahmen, M Helias Physical Review Research 4 (4), 043143, 2022 | 20 | 2022 |
| Learning interacting theories from data C Merger, A René, K Fischer, P Bouss, S Nestler, D Dahmen, ... Physical Review X 13 (4), 041033, 2023 | 6 | 2023 |
| Optimal signal propagation in ResNets through residual scaling K Fischer, D Dahmen, M Helias arXiv preprint arXiv:2305.07715, 2023 | 4 | 2023 |
| Critical feature learning in deep neural networks K Fischer, J Lindner, D Dahmen, Z Ringel, M Krämer, M Helias arXiv preprint arXiv:2405.10761, 2024 | 2 | 2024 |
| From Kernels to Features: A Multi-Scale Adaptive Theory of Feature Learning N Rubin, K Fischer, J Lindner, D Dahmen, I Seroussi, Z Ringel, M Krämer, ... arXiv preprint arXiv:2502.03210, 2025 | 1 | 2025 |
| Nonlinear dimensionality reduction with normalizing flows for analysis of electrophysiological recordings P Bouss, S Nestler, CL Merger, K Fischer, M Helias, A Rene 32nd Annual Computational Neuroscience Meeting, 2023 | | 2023 |
