Kevin K. Huguenin-Dumittan

Overcoming the limitations of body-ordered potentials for atomistic machine learning

Machine-learning interatomic potentials have become indispensable tools in atomistic simulations. The most popular models rely heavily on physical priors, such as locality, smoothness and symmetry, that are assumed to improve the accuracy and transferability of the trained models. However, recent evidence suggests that...