On-the-Fly Bayesian Active Learning of Interpretable Force-Fields for Atomistic Rare Events

1 code implementation • 3 Apr 2019 • Jonathan Vandermause, Steven B. Torrisi, Simon Batzner, Alexie M. Kolpak, Boris Kozinsky

Machine learning based interatomic potentials currently require manual construction of training sets consisting of thousands of first principles calculations and are often restricted to single-component and nonreactive systems.

Computational Physics Materials Science