High-dimensional flow law parameter calibration and uncertainty quantification over Antarctic ice shelves: a variational Bayesian approach using deep learning

Bibliographic Details
Main Authors: Riel, Bryan, Minchew, Brent
Format: Other/Unknown Material
Language:unknown
Published: Wiley 2021
Subjects:
Antarctic
Antarc*
Ice Shelves
Online Access:http://dx.doi.org/10.1002/essoar.10509116.1
id crwiley:10.1002/essoar.10509116.1
record_format openpolar
spelling crwiley:10.1002/essoar.10509116.1 2024-06-02T07:58:25+00:00 High-dimensional flow law parameter calibration and uncertainty quantification over Antarctic ice shelves: a variational Bayesian approach using deep learning Riel, Bryan Minchew, Brent 2021 http://dx.doi.org/10.1002/essoar.10509116.1 unknown Wiley posted-content 2021 crwiley https://doi.org/10.1002/essoar.10509116.1 2024-05-03T11:46:00Z Other/Unknown Material Antarc* Antarctic Ice Shelves Wiley Online Library Antarctic
institution Open Polar
collection Wiley Online Library
op_collection_id crwiley
language unknown
format Other/Unknown Material
author Riel, Bryan
Minchew, Brent
spellingShingle Riel, Bryan
Minchew, Brent
High-dimensional flow law parameter calibration and uncertainty quantification over Antarctic ice shelves: a variational Bayesian approach using deep learning
author_facet Riel, Bryan
Minchew, Brent
author_sort Riel, Bryan
title High-dimensional flow law parameter calibration and uncertainty quantification over Antarctic ice shelves: a variational Bayesian approach using deep learning
title_short High-dimensional flow law parameter calibration and uncertainty quantification over Antarctic ice shelves: a variational Bayesian approach using deep learning
title_full High-dimensional flow law parameter calibration and uncertainty quantification over Antarctic ice shelves: a variational Bayesian approach using deep learning
title_fullStr High-dimensional flow law parameter calibration and uncertainty quantification over Antarctic ice shelves: a variational Bayesian approach using deep learning
title_full_unstemmed High-dimensional flow law parameter calibration and uncertainty quantification over Antarctic ice shelves: a variational Bayesian approach using deep learning
title_sort high-dimensional flow law parameter calibration and uncertainty quantification over antarctic ice shelves: a variational bayesian approach using deep learning
publisher Wiley
publishDate 2021
url http://dx.doi.org/10.1002/essoar.10509116.1
geographic Antarctic
geographic_facet Antarctic
genre Antarc*
Antarctic
Ice Shelves
genre_facet Antarc*
Antarctic
Ice Shelves
op_doi https://doi.org/10.1002/essoar.10509116.1
_version_ 1800741737280307200

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