Machine Learning Interatomic Potentials: library for efficient training, model development and simulation of molecular systems

Christoph Brunken, Olivier Peltre, Heloise Chomet +11

Machine Learning Interatomic Potentials (MLIP) are a novel in silico approach for molecular property prediction, creating an alternative to disrupt the accuracy/speed trade-off of…