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dc.contributor.authorGlau, Ken_US
dc.contributor.authorWunderlich, Len_US
dc.date.accessioned2023-05-03T14:57:12Z
dc.date.available2023-03-20en_US
dc.date.issued2023-04-13en_US
dc.identifier.issn1572-9338en_US
dc.identifier.urihttps://qmro.qmul.ac.uk/xmlui/handle/123456789/86125
dc.format.extent1 - 27en_US
dc.publisherSpringeren_US
dc.relation.ispartofAnnals of Operations Researchen_US
dc.rightsThis item is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
dc.rightsAttribution 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/us/*
dc.titleNeural network expression rates and applications of the deep parametric PDE method in counterparty credit risken_US
dc.typeArticle
dc.rights.holder© 2023 The Author(s). Published by Springer Nature
dc.identifier.doi10.1007/s10479-023-05315-4en_US
pubs.notesNot knownen_US
pubs.publication-statusPublisheden_US
dcterms.dateAccepted2023-03-20en_US
rioxxterms.funderDefault funderen_US
rioxxterms.identifier.projectDefault projecten_US
qmul.funderDeep Learning Reduced Basis Method for High-Dimensional Parametric Partial Differential Equations in Finance::Engineering and Physical Sciences Research Councilen_US


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This item is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Except where otherwise noted, this item's license is described as This item is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.