Gaussian process regression to accelerate geometry optimizations relying on numerical differentiation
Author:
Affiliation:
1. Department of Chemistry, Aarhus Universitet, DK-8000 Aarhus, Denmark
Funder
Danish Council for Idependent Research
Lundbeckfonden
Danish e-Infrastructure Cooperation
Villum Fonden
Publisher
AIP Publishing
Subject
Physical and Theoretical Chemistry,General Physics and Astronomy
Link
http://aip.scitation.org/doi/pdf/10.1063/1.5009347
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1. A consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements H-Pu
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