Correction: A Δ-machine learning approach for force fields, illustrated by a CCSD(T) 4-body correction to the MB-pol water potential

Abstract

Correction for ‘A Δ-machine learning approach for force fields, illustrated by a CCSD(T) 4-body correction to the MB-pol water potential’ by Chen Qu et al., Digital Discovery, 2022, 1, 658–664, https://doi.org/10.1039/D2DD00057A.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jan 01, 2022
Source ID
10.1039/d2dd90021a

Entities

People

  • Apurba Nandi
  • Chen Qu
  • Joel M. Bowman
  • Paul Houston
  • Qi Yu
  • Riccardo Conte

Organizations

  • Army Research Office
  • Cornell University
  • Emory University
  • Georgia Tech
  • National Aeronautics and Space Administration
  • National Science Foundation
  • University of Milan
  • Yale University

Tags

Readers

  • Artificial Intelligence
  • Astronomy and Astrophysics.
  • Environmental Remediation and Restoration.

Technology Areas

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