Guest Editorial: Special Topic on Software for Atomistic Machine Learning

Abstract

A survey of the contributions to the Journal of Chemical Physics' Special Topic on Software for Atomistic Machine Learning.

References in corpus (2)

• ænet-PyTorch: a GPU-supported implementation for machine learning atomic potentials training
• Generating candidates in global optimization algorithms using complementary energy landscapes