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Title: Machine learning of molecular properties: Locality and active learning

Authors:
ORCiD logo [1]; ORCiD logo [1];  [1]
  1. Skolkovo Institute of Science and Technology, Skolkovo Innovation Center, Nobel St. 3, Moscow 143026, Russia
Publication Date:
Sponsoring Org.:
USDOE
OSTI Identifier:
1433745
Grant/Contract Number:  
1150-06_2015
Resource Type:
Publisher's Accepted Manuscript
Journal Name:
Journal of Chemical Physics
Additional Journal Information:
Journal Name: Journal of Chemical Physics Journal Volume: 148 Journal Issue: 24; Journal ID: ISSN 0021-9606
Publisher:
American Institute of Physics
Country of Publication:
United States
Language:
English

Citation Formats

Gubaev, Konstantin, Podryabinkin, Evgeny V., and Shapeev, Alexander V. Machine learning of molecular properties: Locality and active learning. United States: N. p., 2018. Web. doi:10.1063/1.5005095.
Gubaev, Konstantin, Podryabinkin, Evgeny V., & Shapeev, Alexander V. Machine learning of molecular properties: Locality and active learning. United States. doi:10.1063/1.5005095.
Gubaev, Konstantin, Podryabinkin, Evgeny V., and Shapeev, Alexander V. Thu . "Machine learning of molecular properties: Locality and active learning". United States. doi:10.1063/1.5005095.
@article{osti_1433745,
title = {Machine learning of molecular properties: Locality and active learning},
author = {Gubaev, Konstantin and Podryabinkin, Evgeny V. and Shapeev, Alexander V.},
abstractNote = {},
doi = {10.1063/1.5005095},
journal = {Journal of Chemical Physics},
number = 24,
volume = 148,
place = {United States},
year = {2018},
month = {6}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
DOI: 10.1063/1.5005095

Citation Metrics:
Cited by: 14 works
Citation information provided by
Web of Science

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