49 citations · 49 across the 1 of their papers we have counts for
3 papers
physics.chem-ph2021★ 49 cited
Efficient implementation of atom-density representations
Félix Musil, Max Veit, Alexander Goscinski +5
Physically-motivated and mathematically robust atom-centred representations of molecular structures are key to the success of modern atomistic machine learning (ML) methods. They l…
physics.chem-ph2020
Predicting molecular dipole moments by combining atomic partial charges and atomic dipoles
Max Veit, David M. Wilkins, Yang Yang +2
The molecular dipole moment () is a central quantity in chemistry. It is essential in predicting infrared and sum-frequency generation spectra, as well as induction a…
physics.chem-ph2018
Equation of state of fluid methane from first principles with machine learning potentials
Max Veit, Sandeep Kumar Jain, Satyanarayana Bonakala +3
The predictive simulation of molecular liquids requires models that are not only accurate, but computationally efficient enough to handle the large systems and long time scales req…