Bayesian Machine Learning Approach to the Quantification of Uncertainties on Ab Initio Potential Energy Surfaces

Document Details

Document Type
Pub Defense Publication
Publication Date
May 28, 2020
Source ID
10.1021/acs.jpca.0c02395

Entities

People

  • Marco Panesi
  • Richard L. Jaffe
  • S. Venturi

Organizations

  • Air Force Office of Scientific Research
  • Ames Research Center
  • National Aeronautics and Space Administration
  • University of Illinois Urbana–Champaign

Tags

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Neural Networks