| Machine learning for electronically excited states of molecules J Westermayr, P Marquetand Chemical Reviews 121 (16), 9873-9926, 2020 | 352 | 2020 |
| Machine learning enables long time scale molecular photodynamics simulations J Westermayr, M Gastegger, MFSJ Menger, S Mai, L González, ... Chemical science 10 (35), 8100-8107, 2019 | 207 | 2019 |
| Perspective on integrating machine learning into computational chemistry and materials science J Westermayr, M Gastegger, KT Schütt, RJ Maurer The Journal of Chemical Physics 154 (23), 2021 | 189 | 2021 |
| Combining SchNet and SHARC: The SchNarc machine learning approach for excited-state dynamics J Westermayr, M Gastegger, P Marquetand The journal of physical chemistry letters 11 (10), 3828-3834, 2020 | 173 | 2020 |
| Roadmap on machine learning in electronic structure HJ Kulik, T Hammerschmidt, J Schmidt, S Botti, MAL Marques, M Boley, ... Electronic Structure 4 (2), 023004, 2022 | 149 | 2022 |
| Neural networks and kernel ridge regression for excited states dynamics of CH2NH: From single-state to multi-state representations and multi-property machine learning models J Westermayr, FA Faber, AS Christensen, OA von Lilienfeld, ... Machine Learning: Science and Technology 1 (2), 025009, 2020 | 86 | 2020 |
| Machine learning and excited-state molecular dynamics J Westermayr, P Marquetand Machine Learning: Science and Technology 1 (4), 043001, 2020 | 72 | 2020 |
| Deep learning for UV absorption spectra with SchNarc: First steps toward transferability in chemical compound space J Westermayr, P Marquetand The Journal of Chemical Physics 153 (15), 2020 | 69 | 2020 |
| Physically inspired deep learning of molecular excitations and photoemission spectra J Westermayr, RJ Maurer Chemical Science 12 (32), 10755-10764, 2021 | 60 | 2021 |
| High-throughput property-driven generative design of functional organic molecules J Westermayr, J Gilkes, R Barrett, RJ Maurer Nature Computational Science 3 (2), 139-148, 2023 | 48 | 2023 |
| Deep learning study of tyrosine reveals that roaming can lead to photodamage J Westermayr, M Gastegger, D Vörös, L Panzenboeck, F Joerg, ... Nature Chemistry 14 (8), 914-919, 2022 | 46 | 2022 |
| BuRNN: Buffer region neural network approach for polarizable-embedding neural network/molecular mechanics simulations B Lier, P Poliak, P Marquetand, J Westermayr, C Oostenbrink The Journal of Physical Chemistry Letters 13 (17), 3812-3818, 2022 | 38 | 2022 |
| Long-range dispersion-inclusive machine learning potentials for structure search and optimization of hybrid organic–inorganic interfaces J Westermayr, S Chaudhuri, A Jeindl, OT Hofmann, RJ Maurer Digital Discovery 1 (4), 463-475, 2022 | 29 | 2022 |
| Tridentate 3-substituted naphthoquinone ruthenium arene complexes: Synthesis, characterization, aqueous behavior, and theoretical and biological studies H Geisler, J Westermayr, K Cseh, D Wenisch, V Fuchs, S Harringer, ... Inorganic Chemistry 60 (13), 9805-9819, 2021 | 14 | 2021 |
| NQCDynamics. jl: A Julia package for nonadiabatic quantum classical molecular dynamics in the condensed phase J Gardner, OA Douglas-Gallardo, WG Stark, J Westermayr, SM Janke, ... The Journal of Chemical Physics 156 (17), 2022 | 12 | 2022 |
| Machine learning interatomic potentials for reactive hydrogen dynamics at metal surfaces based on iterative refinement of reaction probabilities WG Stark, J Westermayr, OA Douglas-Gallardo, J Gardner, S Habershon, ... The Journal of Physical Chemistry C 127 (50), 24168-24182, 2023 | 11 | 2023 |
| Arene variation of highly cytotoxic tridentate naphthoquinone-based ruthenium (II) complexes and in-depth in vitro studies K Cseh, H Geisler, K Stanojkovska, J Westermayr, P Brunmayr, ... Pharmaceutics 14 (11), 2466, 2022 | 10 | 2022 |
| Reinforcement learning for traversing chemical structure space: Optimizing transition states and minimum energy paths of molecules R Barrett, J Westermayr The Journal of Physical Chemistry Letters 15 (1), 349-356, 2024 | 8 | 2024 |
| Decoding energy decomposition analysis: Machine‐learned Insights on the impact of the density functional on the bonding analysis T Oestereich, R Tonner‐Zech, J Westermayr Journal of Computational Chemistry 45 (7), 368-376, 2024 | 4 | 2024 |
| S pai NN: equivariant message passing for excited-state nonadiabatic molecular dynamics S Mausenberger, C Müller, A Tkatchenko, P Marquetand, L González, ... Chemical Science 15 (38), 15880-15890, 2024 | 3 | 2024 |
Philipp MarquetandVienna, AustriaVerified email at marquetand.net