Geometry-enhanced pretraining on interatomic potentials

Chemistry, Computational Chemistry, Information Science, Computer Science, Artificial Intelligence,
machine learning   molecular dynamics   graph neural networks   self-supervised learning   interatomic potentials  

Geometric Enhanced Pretraining for Interatomic Potentials Introduction Molecular dynamics (MD) simulations play an important role in fields such as physics, chemistry, biology, and materials science, providing insights into atomic-level processes. The accuracy and efficiency of MD simulations depend on the choice of interatomic potential functions ...