2 papers
physics.chem-ph2026
Accurate and Transferable Intermolecular Potential Based on Machine-Learned Molecular Electron Density
Dahvyd Wing, Mihail Bogojeski, Szabolcs Goger +2
Machine-learned force fields (MLFFs) contain many learnable parameters and therefore require large training datasets. This poses a challenge for developing highly accurate, general…
physics.chem-ph2026
Enhancing molecular dynamics with equivariant machine-learned densities
Mihail Bogojeski, Muhammad R. Hasyim, Leslie Vogt-Maranto +3
Machine-learning interatomic potentials (MLIPs) have enabled molecular dynamics at near ab initio accuracy, yet remain limited to energies and forces by construction, leaving elect…