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
Published in: | Journal of Computational Physics |
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Format: | Article in Journal/Newspaper |
Language: | English |
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Elsevier BV
2015
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Online Access: | 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 |
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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 https://api.elsevier.com/content/article/PII:S0021999115003046?httpAccept=text/xml 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 |
_version_ |
1799470621839589376 |