Bayesian Machine Learning Approach to the Quantification of Uncertainties on Ab Initio Potential Energy Surfaces
Author:
Affiliation:
1. University of Illinois at Urbana−Champaign, Urbana, Illinois 61801, United States
2. NASA Ames Research Center, Moffett Field, California 94035-1000, United States
Funder
Air Force Office of Scientific Research
National Aeronautics and Space Administration
Publisher
American Chemical Society (ACS)
Subject
Physical and Theoretical Chemistry
Link
https://pubs.acs.org/doi/pdf/10.1021/acs.jpca.0c02395
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