| Machine learning potentials for metal-organic frameworks using an incremental learning approach S Vandenhaute, M Cools-Ceuppens, S DeKeyser, T Verstraelen, ... npj Computational Materials 9 (1), 1-8, 2023 | 44 | 2023 |
| IOData: A python library for reading, writing, and converting computational chemistry file formats and generating input files T Verstraelen, W Adams, L Pujal, A Tehrani, BD Kelly, L Macaya, F Meng, ... Journal of Computational Chemistry 42 (6), 458-464, 2021 | 22 | 2021 |
| Nuclear quantum effects on zeolite proton hopping kinetics explored with machine learning potentials and path integral molecular dynamics M Bocus, R Goeminne, A Lamaire, M Cools-Ceuppens, T Verstraelen, ... Nature Communications 14 (1), 1008, 2023 | 18 | 2023 |
| Modeling electronic response properties with an explicit-electron machine learning potential M Cools-Ceuppens, J Dambre, T Verstraelen Journal of Chemical Theory and Computation 18 (3), 1672-1691, 2022 | 14 | 2022 |
| Quantum Free Energy Profiles for Molecular Proton Transfers A Lamaire, M Cools-Ceuppens, M Bocus, T Verstraelen, ... Journal of Chemical Theory and Computation 19 (1), 18-24, 2022 | 1 | 2022 |
| Incorporating long-range interactions and polarization in machine learning potentials with explicit electrons M Cools-Ceuppens Ghent University, 2022 | | 2022 |
