| Machine learning interpretable models of cell mechanics from protein images MS Schmitt*, J Colen*, S Sala, J Devany, S Seetharaman, A Caillier, ... Cell, 2024 | 21* | 2024 |
| Geometry adaptation of protrusion and polarity dynamics in confined cell migration DB Brückner, M Schmitt, A Fink, G Ladurner, J Flommersfeld, N Arlt, ... Physical Review X 12 (3), 031041, 2022 | 19 | 2022 |
| Information theory for data-driven model reduction in physics and biology MS Schmitt, M Koch-Janusz, M Fruchart, DS Seara, Rust, Michael, ... arXiv preprint arXiv:2312.06608, 2024 | | 2024 |
| The information bottleneck learns spectral properties of dynamical systems M Schmitt, M Koch-Janusz, M Fruchart, D Seara, V Vitelli Bulletin of the American Physical Society, 2024 | | 2024 |
| Information bottleneck learns dominant transfer operator eigenfunctions in dynamical systems MS Schmitt, M Koch-Janusz, M Fruchart, DS Seara, V Vitelli NeurIPS 2023 ML for the Physical Sciences Workshop, 2023 | | 2023 |
| Information theory for model reduction in stochastic dynamical systems MS Schmitt, M Koch-Janusz, M Fruchart, DS Seara, V Vitelli arXiv preprint arXiv:2312.06608, 2023 | | 2023 |
| Neural networks for data-driven models of cell mechanics M Schmitt, J Colen, S Sala, M Gardel, P Oakes, V Vitelli Bulletin of the American Physical Society, 2023 | | 2023 |
| Machine learning continuum models for cellular force generation M Schmitt, J Colen, S Sala, M Gardel, P Oakes, V Vitelli APS March Meeting Abstracts 2022, A06. 007, 2022 | | 2022 |
| Confined cell migration-a dynamical systems perspective D Brückner, A Fink, M Schmitt, N Arlt, J Rädler, C Broedersz Bulletin of the American Physical Society 65, 2020 | | 2020 |
