Scalable and efficient algorithms for the propagation of uncertainty from data through inference to prediction for large-scale problems, with application to flow of the Antarctic ice sheet

Bibliographic Details
Published in:Journal of Computational Physics
Main Authors: Isaac, Tobin, Petra, Noemi, Stadler, Georg, Ghattas, Omar
Other Authors: Air Force Office of Scientific Research, U.S. Department of Energy, National Science Foundation, Office of Science
Format: Article in Journal/Newspaper
Language:English
Published: Elsevier BV 2015
Subjects:
Computer Science Applications
Physics and Astronomy (miscellaneous)
Applied Mathematics
Computational Mathematics
Modeling and Simulation
Numerical Analysis
Antarc*
Antarctic
Ice Sheet
Online Access:http://dx.doi.org/10.1016/j.jcp.2015.04.047
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spelling crelsevierbv:10.1016/j.jcp.2015.04.047 2024-05-19T07:32:32+00:00 Scalable and efficient algorithms for the propagation of uncertainty from data through inference to prediction for large-scale problems, with application to flow of the Antarctic ice sheet Isaac, Tobin Petra, Noemi Stadler, Georg Ghattas, Omar Air Force Office of Scientific Research U.S. Department of Energy National Science Foundation Office of Science 2015 http://dx.doi.org/10.1016/j.jcp.2015.04.047 https://api.elsevier.com/content/article/PII:S0021999115003046?httpAccept=text/xml https://api.elsevier.com/content/article/PII:S0021999115003046?httpAccept=text/plain en eng Elsevier BV https://www.elsevier.com/tdm/userlicense/1.0/ http://www.elsevier.com/open-access/userlicense/1.0/ Journal of Computational Physics volume 296, page 348-368 ISSN 0021-9991 Computer Science Applications Physics and Astronomy (miscellaneous) Applied Mathematics Computational Mathematics Modeling and Simulation Numerical Analysis journal-article 2015 crelsevierbv https://doi.org/10.1016/j.jcp.2015.04.047 2024-04-22T06:45:38Z Article in Journal/Newspaper Antarc* Antarctic Ice Sheet ScienceDirect (Elsevier) Journal of Computational Physics 296 348 368
institution Open Polar
collection ScienceDirect (Elsevier)
op_collection_id crelsevierbv
language English
topic Computer Science Applications
Physics and Astronomy (miscellaneous)
Applied Mathematics
Computational Mathematics
Modeling and Simulation
Numerical Analysis
spellingShingle Computer Science Applications
Physics and Astronomy (miscellaneous)
Applied Mathematics
Computational Mathematics
Modeling and Simulation
Numerical Analysis
Isaac, Tobin
Petra, Noemi
Stadler, Georg
Ghattas, Omar
Scalable and efficient algorithms for the propagation of uncertainty from data through inference to prediction for large-scale problems, with application to flow of the Antarctic ice sheet
topic_facet Computer Science Applications
Physics and Astronomy (miscellaneous)
Applied Mathematics
Computational Mathematics
Modeling and Simulation
Numerical Analysis
author2 Air Force Office of Scientific Research
U.S. Department of Energy
National Science Foundation
Office of Science
format Article in Journal/Newspaper
author Isaac, Tobin
Petra, Noemi
Stadler, Georg
Ghattas, Omar
author_facet Isaac, Tobin
Petra, Noemi
Stadler, Georg
Ghattas, Omar
author_sort Isaac, Tobin
title Scalable and efficient algorithms for the propagation of uncertainty from data through inference to prediction for large-scale problems, with application to flow of the Antarctic ice sheet
title_short Scalable and efficient algorithms for the propagation of uncertainty from data through inference to prediction for large-scale problems, with application to flow of the Antarctic ice sheet
title_full Scalable and efficient algorithms for the propagation of uncertainty from data through inference to prediction for large-scale problems, with application to flow of the Antarctic ice sheet
title_fullStr Scalable and efficient algorithms for the propagation of uncertainty from data through inference to prediction for large-scale problems, with application to flow of the Antarctic ice sheet
title_full_unstemmed Scalable and efficient algorithms for the propagation of uncertainty from data through inference to prediction for large-scale problems, with application to flow of the Antarctic ice sheet
title_sort scalable and efficient algorithms for the propagation of uncertainty from data through inference to prediction for large-scale problems, with application to flow of the antarctic ice sheet
publisher Elsevier BV
publishDate 2015
url http://dx.doi.org/10.1016/j.jcp.2015.04.047
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https://api.elsevier.com/content/article/PII:S0021999115003046?httpAccept=text/plain
genre Antarc*
Antarctic
Ice Sheet
genre_facet Antarc*
Antarctic
Ice Sheet
op_source Journal of Computational Physics
volume 296, page 348-368
ISSN 0021-9991
op_rights https://www.elsevier.com/tdm/userlicense/1.0/
http://www.elsevier.com/open-access/userlicense/1.0/
op_doi https://doi.org/10.1016/j.jcp.2015.04.047
container_title Journal of Computational Physics
container_volume 296
container_start_page 348
op_container_end_page 368
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