Batzner, Simon

E(3)-equivariant graph neural networks for data-efficient and accurate interatomic potentials

Batzner, S., Musaelian, A., Sun, L., Geiger, M., Mailoa, J. P., Kornbluth, M., Molinari, N., Smidt, T. E., & Kozinsky, B. (2022) · Nature Communications

Machine Learning in Materials ScienceAdvanced Chemical Physics Studies

Cited by 2,285

Scaling deep learning for materials discovery

Merchant, A., Batzner, S., Schoenholz, S. S., Aykol, M., Cheon, G., & Cubuk, E. D. (2023) · Nature

Machine Learning in Materials ScienceAdvanced Chemical Physics Studies

Cited by 1,527

On-the-fly active learning of interpretable Bayesian force fields for atomistic rare events

Vandermause, J., Torrisi, S. B., Batzner, S., Xie, Y., Sun, L., Kolpak, A. M., & Kozinsky, B. (2020) · npj Computational Materials

Machine Learning in Materials ScienceAdvanced Chemical Physics Studies

Cited by 459