Richard A. Messerly

According to our database, Richard A. Messerly authored at least 6 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Multi-fidelity learning for interatomic potentials: low-level forces and high-level energies are all you need^*.

Mitchell Messerly, Sakib Matin, Alice E. A. Allen, Benjamin T. Nebgen, Kipton Barros, Justin S. Smith, Nicholas Lubbers, Richard A. Messerly

Mach. Learn. Sci. Technol., 2025

Toward machine learning interatomic potentials for modeling uranium mononitride.

Lorena Alzate-Vargas, Kashi N. Subedi, Nicholas Lubbers, Michael W. D. Cooper, Roxanne M. Tutchton, Tammie Gibson, Richard A. Messerly

Mach. Learn. Sci. Technol., 2025

Including Physics-Informed Atomization Constraints in Neural Networks for Reactive Chemistry.

Shuhao Zhang, Michael Chigaev, Olexandr Isayev, Richard A. Messerly, Nicholas Lubbers

J. Chem. Inf. Model., 2025

Improving Bond Dissociations of Reactive Machine Learning Potentials through Physics-Constrained Data Augmentation.

Luan G. F. dos Santos, Benjamin T. Nebgen, Alice E. A. Allen, Brenden W. Hamilton, Sakib Matin, Justin S. Smith, Richard A. Messerly

J. Chem. Inf. Model., 2025

2023

Uncertainty-driven dynamics for active learning of interatomic potentials.

Maksim Kulichenko, Kipton Barros, Nicholas Lubbers, Ying Wai Li, Richard A. Messerly, Sergei Tretiak, Justin S. Smith, Benjamin T. Nebgen

Nat. Comput. Sci., 2023

2022

Bayesian-Inference-Driven Model Parametrization and Model Selection for 2CLJQ Fluid Models.

Owen Madin, Simon Boothroyd, Richard A. Messerly, Josh Fass, John D. Chodera, Michael R. Shirts

J. Chem. Inf. Model., 2022