Assessing Gaussian Process Regression and Permutationally Invariant Polynomial Approaches To Represent High-Dimensional Potential Energy Surfaces

Published 2018 View Full Article

  1. Home
  2. Publications
  3. Publication Search
  4. Publication Details
Title
Assessing Gaussian Process Regression and Permutationally Invariant Polynomial Approaches To Represent High-Dimensional Potential Energy Surfaces
Authors
Keywords
-
Journal
Journal of Chemical Theory and Computation
Volume 14, Issue 7, Pages 3381-3396
Publisher
American Chemical Society (ACS)
Online
2018-05-31
DOI
10.1021/acs.jctc.8b00298

Ask authors/readers for more resources

Protocol

Community support

Reagent

Community support

Reprint

Contact the author

Find Funding. Review Successful Grants.

Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.

Explore

Discover Peeref hubs

Discuss science. Find collaborators. Network.

Join a conversation
Webinars Posters Questions Hubs Funding Journals Articles Connect Collections Reviewers About Us FAQs Mobile App Privacy Policy Terms of Use
© Peeref 2019-2024. All rights reserved.