Benchmarking Compositional Generalisation for Machine Learning Interatomic Potentials
arXiv:2605.08988v1 Announce Type: cross
Abstract: Machine Learning Interatomic Potentials play a fundamental role in computational chemistry and materials science, enabling applications from molecular dynamics simulations to drug design and materials …