Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules N Gebauer, M Gastegger, K Schütt Advances in Neural Information Processing Systems 32, 7566-7578, 2019 | 232 | 2019 |
Inverse design of 3d molecular structures with conditional generative neural networks NWA Gebauer, M Gastegger, SSP Hessmann, KR Müller, KT Schütt Nature communications 13 (1), 973, 2022 | 157 | 2022 |
Generating equilibrium molecules with deep neural networks NWA Gebauer, M Gastegger, KT Schütt NeurIPS Workshop on Machine Learning for Molecules and Materials 2018, 2018 | 42 | 2018 |
SchNetPack 2.0: A neural network toolbox for atomistic machine learning KT Schütt, SSP Hessmann, NWA Gebauer, J Lederer, M Gastegger The Journal of Chemical Physics 158 (14), 2023 | 40 | 2023 |
3D-Scaffold: A deep learning framework to generate 3d coordinates of drug-like molecules with desired scaffolds RP Joshi, NWA Gebauer, M Bontha, M Khazaieli, RM James, JB Brown, ... The Journal of Physical Chemistry B 125 (44), 12166-12176, 2021 | 34 | 2021 |
Molecular relaxation by reverse diffusion with time step prediction K Kahouli, SSP Hessmann, KR Müller, S Nakajima, S Gugler, ... Machine Learning: Science and Technology, 2024 | 2 | 2024 |
Accelerating crystal structure search through active learning with neural networks for rapid relaxations SSP Hessmann, KT Schütt, NWA Gebauer, M Gastegger, T Oguchi, ... arXiv preprint arXiv:2408.04073, 2024 | | 2024 |