Xie, Yu

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

Scalable emulation of protein equilibrium ensembles with generative deep learning

Lewis, S., Hempel, T., Jiménez-Luna, J., Gastegger, M., Xie, Y., Foong, A. Y. K., Satorras, V. G., Abdin, O., Veeling, B. S., Zaporozhets, I., et al. (2025) · Science

Protein Structure and DynamicsComputational Drug Discovery Methods

Cited by 390

Scalable emulation of protein equilibrium ensembles with generative deep learning

Lewis, S., Hempel, T., Jiménez Luna, J., Gastegger, M., Xie, Y., Foong, A. Y. K., García Satorras, V., Abdin, O., Veeling, B. S., Zaporozhets, I., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory)

Protein Structure and DynamicsComputational Drug Discovery Methods

Cited by 349

Active learning of reactive Bayesian force fields applied to heterogeneous catalysis dynamics of H/Pt

Vandermause, J., Xie, Y., Lim, J. S., Owen, C. J., & Kozinsky, B. (2022) · Nature Communications

Machine Learning in Materials ScienceAdvanced Chemical Physics Studies

Cited by 147