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• Micron-scale heterogeneous catalysis with Bayesian force fields from first principles and active learning
  2022 · 24 citations
• Learning Local Equivariant Representations for Large-Scale Atomistic Dynamics
  2022 · 22 citations
• Overcoming the Size Limit of First Principles Molecular Dynamics Simulations with an In-Distribution Substructure Embedding Active Learner
  2023 · 3 citations
• Complexity of Many-Body Interactions in Transition Metals via Machine-Learned Force Fields from the TM23 Data Set
  2023 · 2 citations
• Multitask machine learning of collective variables for enhanced sampling of rare events
  2020
• Driving atomic structures of molecules, crystals, and complex systems with local similarity kernels
  2022