245 citations · 2.1k across the 36 of their papers we have counts for
22 papers · 1 filter
Molecular-orbital-based Machine Learning for Open-shell and Multi-reference Systems with Kernel Addition Gaussian Process Regression
Lixue Cheng, Jiace Sun, J. Emiliano Deustua +2
We introduce a novel machine learning strategy, kernel addition Gaussian process regression (KA-GPR), in molecular-orbital-based machine learning (MOB-ML) to learn the total correl…
Molecular Dipole Moment Learning via Rotationally Equivariant Gaussian Process Regression with Derivatives in Molecular-orbital-based Machine Learning
Jiace Sun, Lixue Cheng, Thomas F. Miller
This study extends the accurate and transferable molecular-orbital-based machine learning (MOB-ML) approach to modeling the contribution of electron correlation to dipole moments a…
Accurate Molecular-Orbital-Based Machine Learning Energies via Unsupervised Clustering of Chemical Space
Lixue Cheng, Jiace Sun, Thomas F. Miller
We introduce an unsupervised clustering algorithm to improve training efficiency and accuracy in predicting energies using molecular-orbital-based machine learning (MOB-ML). This w…
Equilibrium-nonequilibrium ring-polymer molecular dynamics for nonlinear spectroscopy
Tomislav Begušić, Xuecheng Tao, Geoffrey A. Blake +1
Two-dimensional Raman and hybrid terahertz/Raman spectroscopic techniques provide invaluable insight into molecular structure and dynamics of condensed-phase systems. However, corr…
Molecular Energy Learning Using Alternative Blackbox Matrix-Matrix Multiplication Algorithm for Exact Gaussian Process
Jiace Sun, Lixue Cheng, Thomas F. Miller
We present an application of the blackbox matrix-matrix multiplication (BBMM) algorithm to scale up the Gaussian Process (GP) training of molecular energies in the molecular-orbita…
OrbNet Denali: A machine learning potential for biological and organic chemistry with semi-empirical cost and DFT accuracy
Anders S. Christensen, Sai Krishna Sirumalla, Zhuoran Qiao +8
We present OrbNet Denali, a machine learning model for electronic structure that is designed as a drop-in replacement for ground-state density functional theory (DFT) energy calcul…