75 citations · 314 across the 14 of their papers we have counts for
3 papers · 1 filter
A CCSD(T)-based permutationally invariant polynomial 4-body potential for water
Apurba Nandi, Chen Qu, Paul L. Houston +2
We report a permutationally invariant polynomial (PIP) potential energy surface for the water 4-body interaction. This 12-atom PES is a fit to 2119, symmetry-unique, CCSD(T)-F12a/h…
Breaking the Coupled Cluster Barrier for Machine Learned Potentials of Large Molecules: The Case of 15-atom Acetylacetone
Chen Qu, Paul Houston, Riccardo Conte +2
Machine-learned potential energy surfaces (PESs) for molecules with more than 10 atoms are typically forced to use lower-level electronic structure methods such as density function…
Machine Learning for Vibrational Spectroscopy via Divide-and-Conquer Semiclassical Initial Value Representation Molecular Dynamics with Application to N-Methylacetamide
Michele Gandolfi, Alessandro Rognoni, Chiara Aieta +2
A machine learning algorithm for partitioning the nuclear vibrational space into subspaces is introduced. The subdivision criterion is based on Liouville's theorem, i.e. best prese…