Comment on %22Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning%22.
Abstract
Abstract not provided.
- Authors:
- Publication Date:
- Research Org.:
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Org.:
- USDOE National Nuclear Security Administration (NNSA)
- OSTI Identifier:
- 1145302
- Report Number(s):
- SAND2012-0918J
Journal ID: ISSN 0031--9007; 442255
- DOE Contract Number:
- DE-AC04-94AL85000
- Resource Type:
- Journal Article
- Journal Name:
- Physical Review Letters
- Additional Journal Information:
- Journal Volume: 109; Journal Issue: 5; Related Information: Proposed for publication in Physical Review Letters.; Journal ID: ISSN 0031--9007
- Country of Publication:
- United States
- Language:
- English
Citation Formats
Moussa, Jonathan Edward. Comment on %22Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning%22.. United States: N. p., 2012.
Web. doi:10.1103/PhysRevLett.109.059801.
Moussa, Jonathan Edward. Comment on %22Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning%22.. United States. https://doi.org/10.1103/PhysRevLett.109.059801
Moussa, Jonathan Edward. Wed .
"Comment on %22Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning%22.". United States. https://doi.org/10.1103/PhysRevLett.109.059801.
@article{osti_1145302,
title = {Comment on %22Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning%22.},
author = {Moussa, Jonathan Edward},
abstractNote = {Abstract not provided.},
doi = {10.1103/PhysRevLett.109.059801},
url = {https://www.osti.gov/biblio/1145302},
journal = {Physical Review Letters},
issn = {0031--9007},
number = 5,
volume = 109,
place = {United States},
year = {2012},
month = {2}
}
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