| On-the-fly active learning of interpretable Bayesian force fields for atomistic rare events J Vandermause, SB Torrisi, S Batzner, Y Xie, L Sun, AM Kolpak, ... npj Computational Materials 6 (1), 20, 2020 | 286 | 2020 |
| Accurate and scalable graph neural network force field and molecular dynamics with direct force architecture CW Park, M Kornbluth, J Vandermause, C Wolverton, B Kozinsky, ... npj Computational Materials 7 (1), 73, 2021 | 95 | 2021 |
| Active learning of reactive Bayesian force fields applied to heterogeneous catalysis dynamics of H/Pt J Vandermause, Y Xie, JS Lim, CJ Owen, B Kozinsky Nature Communications 13 (1), 5183, 2022 | 82 | 2022 |
| Evolution of metastable structures at bimetallic surfaces from microscopy and machine-learning molecular dynamics JS Lim, J Vandermause, MA Van Spronsen, A Musaelian, Y Xie, L Sun, ... Journal of the American Chemical Society 142 (37), 15907-15916, 2020 | 64 | 2020 |
| Bayesian force fields from active learning for simulation of inter-dimensional transformation of stanene Y Xie, J Vandermause, L Sun, A Cepellotti, B Kozinsky npj Computational Materials 7 (1), 40, 2021 | 56 | 2021 |
| A fast neural network approach for direct covariant forces prediction in complex multi-element extended systems JP Mailoa, M Kornbluth, S Batzner, G Samsonidze, ST Lam, ... Nature machine intelligence 1 (10), 471-479, 2019 | 55 | 2019 |
| Multitask machine learning of collective variables for enhanced sampling of rare events L Sun, J Vandermause, S Batzner, Y Xie, D Clark, W Chen, B Kozinsky Journal of Chemical Theory and Computation 18 (4), 2341-2353, 2022 | 37 | 2022 |
| Uncertainty-aware molecular dynamics from Bayesian active learning for phase transformations and thermal transport in SiC Y Xie, J Vandermause, S Ramakers, NH Protik, A Johansson, B Kozinsky npj Computational Materials 9 (1), 36, 2023 | 33 | 2023 |
| Micron-scale heterogeneous catalysis with Bayesian force fields from first principles and active learning A Johansson, Y Xie, CJ Owen, J Soo, L Sun, J Vandermause, B Kozinsky arXiv preprint arXiv:2204.12573, 2022 | 13 | 2022 |
| Superadiabatic control of quantum operations J Vandermause, C Ramanathan Physical Review A 93 (5), 052329, 2016 | 10 | 2016 |
| Uncertainty Driven Active Learning of Coarse Grained Free Energy Models BR Duschatko, J Vandermause, N Molinari, B Kozinsky arXiv preprint arXiv:2210.16364, 2022 | 5 | 2022 |
| Unraveling the Catalytic Effect of Hydrogen Adsorption on Pt Nanoparticle Shape-Change CJ Owen, N Marcella, Y Xie, J Vandermause, AI Frenkel, RG Nuzzo, ... arXiv preprint arXiv:2306.00901, 2023 | 4 | 2023 |
| Phase discovery with active learning: Application to structural phase transitions in equiatomic NiTi J Vandermause, A Johansson, Y Miao, JJ Vlassak, B Kozinsky arXiv preprint arXiv:2401.05568, 2024 | 1 | 2024 |
| Active Learning of Bayesian Force Fields J Vandermause Harvard University, 2022 | | 2022 |
