82 citations · 362 across the 7 of their papers we have counts for
Showing 2020Show all
2 papers · 1 filter
physics.chem-ph2020★ 15 cited
Analytical Gradients for Molecular-Orbital-Based Machine Learning
Sebastian J. R. Lee, Tamara Husch, Feizhi Ding +1
Molecular-orbital-based machine learning (MOB-ML) enables the prediction of accurate correlation energies at the cost of obtaining molecular orbitals. Here, we present the derivati…
physics.chem-ph2020★ 53 cited
Improved accuracy and transferability of molecular-orbital-based machine learning: Organics, transition-metal complexes, non-covalent interactions, and transition states
Tamara Husch, Jiace Sun, Lixue Cheng +2
Molecular-orbital-based machine learning (MOB-ML) provides a general framework for the prediction of accurate correlation energies at the cost of obtaining molecular orbitals. We d…