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physics.comp-ph2025
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 +5
The promise of machine learning interatomic potentials (MLIPs) has led to an abundance of public quantum mechanical (QM) training datasets. The quality of an MLIP is directly limit…
physics.comp-ph2021
Bayesian inference-driven model parameterization and model selection for 2CLJQ fluid models
Owen C. Madin, Simon Boothroyd, Richard A. Messerly +3
A high level of physical detail in a molecular model improves its ability to perform high accuracy simulations, but can also significantly affect its complexity and computational c…