| Learning local equivariant representations for large-scale atomistic dynamics A Musaelian, S Batzner, A Johansson, L Sun, CJ Owen, M Kornbluth, ... Nature Communications 14 (1), 579, 2023 | 138 | 2023 |
| Phoebe: a high-performance framework for solving phonon and electron Boltzmann transport equations A Cepellotti, J Coulter, A Johansson, NS Fedorova, B Kozinsky Journal of Physics: Materials 5 (3), 035003, 2022 | 13* | 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 | 11 | 2023 |
| Scaling the leading accuracy of deep equivariant models to biomolecular simulations of realistic size A Musaelian, A Johansson, S Batzner, B Kozinsky arXiv preprint arXiv:2304.10061, 2023 | 10 | 2023 |
| Micron-scale heterogeneous catalysis with Bayesian force fields from first principles and active learning A Johansson, Y Xie, CJ Owen, JS Lim, L Sun, J Vandermause, ... arXiv preprint arXiv:2204.12573, 2022 | 7 | 2022 |
| Learning Interatomic Potentials at Multiple Scales X Fu, A Musaelian, A Johansson, T Jaakkola, B Kozinsky arXiv preprint arXiv:2310.13756, 2023 | | 2023 |
| Stability, mechanisms and kinetics of emergence of Au surface reconstructions using Bayesian force fields CJ Owen, Y Xie, A Johansson, L Sun, B Kozinsky arXiv preprint arXiv:2308.07311, 2023 | | 2023 |
| Atomistic Modelling of Creep and Flow in Silica-Water Systems A Johansson | | 2019 |
Boris KozinskyHarvard UniversityVerified email at seas.harvard.edu
