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Title: Predictive Fidelity of Machine Learning Methods Applied to Scientific Simulations.

Abstract

Abstract not provided.

Authors:
; ; ; ; ;
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)
OSTI Identifier:
1512381
Report Number(s):
SAND2018-0141C
659775
DOE Contract Number:  
AC04-94AL85000
Resource Type:
Conference
Resource Relation:
Conference: Proposed for presentation at the Scientific Machine Learning Workshop held January 30 - February 1, 2018 in North Bethesda, MD.
Country of Publication:
United States
Language:
English

Citation Formats

Debusschere, Bert, Templeton, Jeremy Alan, Safta, Cosmin, Sargsyan, Khachik, Pinar, Ali, and Najm, Habib N. Predictive Fidelity of Machine Learning Methods Applied to Scientific Simulations.. United States: N. p., 2018. Web.
Debusschere, Bert, Templeton, Jeremy Alan, Safta, Cosmin, Sargsyan, Khachik, Pinar, Ali, & Najm, Habib N. Predictive Fidelity of Machine Learning Methods Applied to Scientific Simulations.. United States.
Debusschere, Bert, Templeton, Jeremy Alan, Safta, Cosmin, Sargsyan, Khachik, Pinar, Ali, and Najm, Habib N. Mon . "Predictive Fidelity of Machine Learning Methods Applied to Scientific Simulations.". United States. https://www.osti.gov/servlets/purl/1512381.
@article{osti_1512381,
title = {Predictive Fidelity of Machine Learning Methods Applied to Scientific Simulations.},
author = {Debusschere, Bert and Templeton, Jeremy Alan and Safta, Cosmin and Sargsyan, Khachik and Pinar, Ali and Najm, Habib N.},
abstractNote = {Abstract not provided.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2018},
month = {1}
}

Conference:
Other availability
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