3 papers
physics.chem-ph2026
Regularity Priors for the Linear Atomic Cluster Expansion
James P. Darby, Joe D. Morrow, Albert P. Bartók +3
Machine-learned interatomic potentials enable large systems to be simulated for long time scales at near ab-initio accuracy. This accuracy is achieved by fitting extremely flexible…
physics.chem-ph2025
Global properties of the energy landscape: a testing and training arena for machine learned potentials
Vlad CÄrare, Fabian L. Thiemann, Joe Morrow +3
Machine learning interatomic potentials (MLIPs) have achieved remarkable accuracy on standard benchmarks, yet their ability to reproduce molecular kinetics -- critical for reaction…
physics.comp-ph2024
An automated framework for exploring and learning potential-energy surfaces
Yuanbin Liu, Joe D. Morrow, Christina Ertural +6
Machine learning has become ubiquitous in materials modelling and now routinely enables large-scale atomistic simulations with quantum-mechanical accuracy. However, developing mach…