| PyEMMA 2: A software package for estimation, validation, and analysis of Markov models MK Scherer, B Trendelkamp-Schroer, F Paul, G Pérez-Hernández, ... Journal of chemical theory and computation 11 (11), 5525-5542, 2015 | 982 | 2015 |
| An open-source drug discovery platform enables ultra-large virtual screens C Gorgulla, A Boeszoermenyi, ZF Wang, PD Fischer, PW Coote, ... Nature 580 (7805), 663-668, 2020 | 438 | 2020 |
| Reactive SINDy: Discovering governing reactions from concentration data M Hoffmann, C Fröhner, F Noé The Journal of chemical physics 150 (2), 2019 | 131 | 2019 |
| Deeptime: a Python library for machine learning dynamical models from time series data M Hoffmann, M Scherer, T Hempel, A Mardt, B de Silva, BE Husic, S Klus, ... Machine Learning: Science and Technology 3 (1), 015009, 2021 | 75 | 2021 |
| ReaDDy 2: Fast and flexible software framework for interacting-particle reaction dynamics M Hoffmann, C Fröhner, F Noé PLoS computational biology 15 (2), e1006830, 2019 | 73 | 2019 |
| Generating valid euclidean distance matrices M Hoffmann, F Noé arXiv preprint arXiv:1910.03131, 2019 | 66 | 2019 |
| Variational selection of features for molecular kinetics MK Scherer, BE Husic, M Hoffmann, F Paul, H Wu, F Noé The Journal of chemical physics 150 (19), 2019 | 61 | 2019 |
| Temporally coherent backmapping of molecular trajectories from coarse-grained to atomistic resolution K Shmilovich, M Stieffenhofer, NE Charron, M Hoffmann The Journal of Physical Chemistry A 126 (48), 9124-9139, 2022 | 8 | 2022 |
| The Navier–Stokes–Darcy problem M Hoffmann Weierstrass Institute, Germany, 2013 | 5 | 2013 |
| Efficient algorithms for simulation and analysis of many-body systems M Hoffmann PQDT-Global, 2022 | | 2022 |
Noe FrankMicrosoft ResearchVerified email at fu-berlin.de
