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Title: Derivative-based uncertainty quantification: automatic differentiation tools for SAS.

Authors:
; ;  [1]
  1. Mathematics and Computer Science
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1055419
Report Number(s):
ANL/MCS-TM-328
DOE Contract Number:  
DE-AC02-06CH11357
Resource Type:
Technical Report
Country of Publication:
United States
Language:
ENGLISH

Citation Formats

Roderick, O, Anitescu, M, and Utke, J. Derivative-based uncertainty quantification: automatic differentiation tools for SAS.. United States: N. p., 2012. Web. doi:10.2172/1055419.
Roderick, O, Anitescu, M, & Utke, J. Derivative-based uncertainty quantification: automatic differentiation tools for SAS.. United States. doi:10.2172/1055419.
Roderick, O, Anitescu, M, and Utke, J. Fri . "Derivative-based uncertainty quantification: automatic differentiation tools for SAS.". United States. doi:10.2172/1055419. https://www.osti.gov/servlets/purl/1055419.
@article{osti_1055419,
title = {Derivative-based uncertainty quantification: automatic differentiation tools for SAS.},
author = {Roderick, O and Anitescu, M and Utke, J},
abstractNote = {},
doi = {10.2172/1055419},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2012},
month = {11}
}

Technical Report:

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