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Title: Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning

Authors:
; ; ;  [1]
  1. LCF
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
SC OFFICE OF BASIC ENERGY SCIENCES
OSTI Identifier:
1121027
Report Number(s):
ANL/LCF/JA-71786
Journal ID: 0031-9007
DOE Contract Number:  
DE-AC02-06CH11357
Resource Type:
Journal Article
Journal Name:
Physical Review Letters
Additional Journal Information:
Journal Volume: 108; Journal Issue: 5 ; 2012
Country of Publication:
United States
Language:
ENGLISH

Citation Formats

Rupp, M., Tkatchenko, A., Muller, Klaus-Robert, and Anatole von Lilienfeld, O. Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning. United States: N. p., 2012. Web. doi:10.1103/PhysRevLett.108.058301.
Rupp, M., Tkatchenko, A., Muller, Klaus-Robert, & Anatole von Lilienfeld, O. Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning. United States. https://doi.org/10.1103/PhysRevLett.108.058301
Rupp, M., Tkatchenko, A., Muller, Klaus-Robert, and Anatole von Lilienfeld, O. Sun . "Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning". United States. https://doi.org/10.1103/PhysRevLett.108.058301.
@article{osti_1121027,
title = {Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning},
author = {Rupp, M. and Tkatchenko, A. and Muller, Klaus-Robert and Anatole von Lilienfeld, O.},
abstractNote = {},
doi = {10.1103/PhysRevLett.108.058301},
url = {https://www.osti.gov/biblio/1121027}, journal = {Physical Review Letters},
number = 5 ; 2012,
volume = 108,
place = {United States},
year = {2012},
month = {1}
}