112 citations · 112 across the 1 of their papers we have counts for
3 papers
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…
A Universal Density Matrix Functional from Molecular Orbital-Based Machine Learning: Transferability across Organic Molecules
Lixue Cheng, Matthew Welborn, Anders S. Christensen +1
We address the degree to which machine learning can be used to accurately and transferably predict post-Hartree-Fock correlation energies. Refined strategies for feature design and…
Transferability in Machine Learning for Electronic Structure via the Molecular Orbital Basis
Matthew Welborn, Lixue Cheng, Thomas F. Miller
We present a machine learning (ML) method for predicting electronic structure correlation energies using Hartree-Fock input.The total correlation energy is expressed in terms of in…