| Molecular dynamics simulations of membrane permeability RM Venable, A Kramer, RW Pastor Chemical reviews 119 (9), 5954-5997, 2019 | 289 | 2019 |
| TorchMD: A deep learning framework for molecular simulations S Doerr, M Majewski, A Pérez, A Kramer, C Clementi, F Noe, T Giorgino, ... Journal of chemical theory and computation 17 (4), 2355-2363, 2021 | 184 | 2021 |
| Coarse graining molecular dynamics with graph neural networks BE Husic, NE Charron, D Lemm, J Wang, A Pérez, M Majewski, A Krämer, ... The Journal of chemical physics 153 (19), 2020 | 167 | 2020 |
| Permeability of membranes in the liquid ordered and liquid disordered phases A Ghysels, A Krämer, RM Venable, WE Teague Jr, E Lyman, K Gawrisch, ... Nature communications 10 (1), 5616, 2019 | 102 | 2019 |
| Semi-Lagrangian off-lattice Boltzmann method for weakly compressible flows A Krämer, K Küllmer, D Reith, W Joppich, H Foysi Physical Review E 95 (2), 023305, 2017 | 67 | 2017 |
| Flow-matching: Efficient coarse-graining of molecular dynamics without forces J Kohler, Y Chen, A Kramer, C Clementi, F Noé Journal of Chemical Theory and Computation 19 (3), 942-952, 2023 | 63 | 2023 |
| CHARMM36 lipid force field with explicit treatment of long-range dispersion: parametrization and validation for phosphatidylethanolamine, phosphatidylglycerol, and ether lipids Y Yu, A Kramer, RM Venable, BR Brooks, JB Klauda, RW Pastor Journal of chemical theory and computation 17 (3), 1581-1595, 2021 | 63 | 2021 |
| Membrane permeability of small molecules from unbiased molecular dynamics simulations A Krämer, A Ghysels, E Wang, RM Venable, JB Klauda, BR Brooks, ... The Journal of Chemical Physics 153 (12), 2020 | 62 | 2020 |
| Smooth normalizing flows J Köhler, A Krämer, F Noé Advances in Neural Information Processing Systems 34, 2796-2809, 2021 | 57 | 2021 |
| Machine learning implicit solvation for molecular dynamics Y Chen, A Krämer, NE Charron, BE Husic, C Clementi, F Noé The Journal of Chemical Physics 155 (8), 2021 | 57 | 2021 |
| OpenMM 8: molecular dynamics simulation with machine learning potentials P Eastman, R Galvelis, RP Peláez, CRA Abreu, SE Farr, E Gallicchio, ... The Journal of Physical Chemistry B 128 (1), 109-116, 2023 | 53 | 2023 |
| Semi-automated optimization of the CHARMM36 lipid force field to include explicit treatment of long-range dispersion Y Yu, A Kramer, RM Venable, AC Simmonett, AD MacKerell Jr, JB Klauda, ... Journal of chemical theory and computation 17 (3), 1562-1580, 2021 | 51 | 2021 |
| Equivariant flow matching L Klein, A Krämer, F Noé Advances in Neural Information Processing Systems 36, 2024 | 43 | 2024 |
| Semi-Lagrangian lattice Boltzmann method for compressible flows D Wilde, A Krämer, D Reith, H Foysi Physical Review E 101 (5), 053306, 2020 | 43 | 2020 |
| Temperature steerable flows and Boltzmann generators M Dibak, L Klein, A Krämer, F Noé Physical Review Research 4 (4), L042005, 2022 | 37 | 2022 |
| Skipping the replica exchange ladder with normalizing flows M Invernizzi, A Krämer, C Clementi, F Noé The Journal of Physical Chemistry Letters 13 (50), 11643-11649, 2022 | 32 | 2022 |
| Multistep lattice Boltzmann methods: Theory and applications D Wilde, A Krämer, K Küllmer, H Foysi, D Reith International Journal for Numerical Methods in Fluids 90 (3), 156-169, 2019 | 32 | 2019 |
| Pseudoentropic derivation of the regularized lattice Boltzmann method A Krämer, D Wilde, K Küllmer, D Reith, H Foysi Physical Review E 100 (2), 023302, 2019 | 26 | 2019 |
| Interactions of water and alkanes: Modifying additive force fields to account for polarization effects A Krämer, FC Pickard IV, J Huang, RM Venable, AC Simmonett, D Reith, ... Journal of chemical theory and computation 15 (6), 3854-3867, 2019 | 26 | 2019 |
| Automated parameterization of intermolecular pair potentials using global optimization techniques A Krämer, M Hülsmann, T Köddermann, D Reith Computer Physics Communications 185 (12), 3228-3239, 2014 | 23 | 2014 |
Noe FrankMicrosoft ResearchVerified email at microsoft.com