| Solving the electronic Schrödinger equation for multiple nuclear geometries with weight-sharing deep neural networks M Scherbela, R Reisenhofer, L Gerard, P Marquetand, P Grohs Nature Computational Science 2 (5), 331-341, 2022 | 60 | 2022 |
| Gold-standard solutions to the Schrödinger equation using deep learning: How much physics do we need? L Gerard, M Scherbela, P Marquetand, P Grohs Advances in Neural Information Processing Systems 35, 10282-10294, 2022 | 40 | 2022 |
| Towards a transferable fermionic neural wavefunction for molecules M Scherbela, L Gerard, P Grohs Nature Communications 15 (1), 120, 2024 | 28* | 2024 |
| Variational Monte Carlo on a Budget—Fine-tuning pre-trained Neural Wavefunctions M Scherbela, L Gerard, P Grohs Advances in Neural Information Processing Systems 36, 23902-23920, 2023 | 8 | 2023 |
| Deep learning variational Monte Carlo for solving the electronic Schrödinger equation L Gerard, P Grohs, M Scherbela Elsevier, 2024 | 1 | 2024 |
| Transferable Neural Wavefunctions for Solids L Gerard, M Scherbela, H Sutterud, M Foulkes, P Grohs arXiv preprint arXiv:2405.07599, 2024 | 1 | 2024 |
