Non-intrusive tensor reconstruction for high dimensional random PDEs
dc.bibliographicCitation.seriesTitle | WIAS Preprints | eng |
dc.bibliographicCitation.volume | 2444 | |
dc.contributor.author | Eigel, Martin | |
dc.contributor.author | Neumann, Johannes | |
dc.contributor.author | Schneider, Reinhold | |
dc.contributor.author | Wolf, Sebastian | |
dc.date.accessioned | 2017-11-14T00:49:27Z | |
dc.date.available | 2019-06-28T08:06:33Z | |
dc.date.issued | 2017 | |
dc.description.abstract | This paper examines a completely non-intrusive, sample-based method for the computation of functional low-rank solutions of high dimensional parametric random PDEs which have become an area of intensive research in Uncertainty Quantification (UQ). In order to obtain a generalized polynomial chaos representation of the approximate stochastic solution, a novel black-box rank-adapted tensor reconstruction procedure is proposed. The performance of the described approach is illustrated with several numerical examples and compared to Monte Carlo sampling. | eng |
dc.description.version | publishedVersion | eng |
dc.format | application/pdf | |
dc.identifier.issn | 2198-5855 | |
dc.identifier.uri | https://doi.org/10.34657/2719 | |
dc.identifier.uri | https://oa.tib.eu/renate/handle/123456789/2419 | |
dc.language.iso | eng | eng |
dc.publisher | Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik | eng |
dc.relation.doi | https://doi.org/10.20347/WIAS.PREPRINT.2444 | |
dc.relation.issn | 0946-8633 | eng |
dc.rights.license | This document may be downloaded, read, stored and printed for your own use within the limits of § 53 UrhG but it may not be distributed via the internet or passed on to external parties. | eng |
dc.rights.license | Dieses Dokument darf im Rahmen von § 53 UrhG zum eigenen Gebrauch kostenfrei heruntergeladen, gelesen, gespeichert und ausgedruckt, aber nicht im Internet bereitgestellt oder an Außenstehende weitergegeben werden. | ger |
dc.subject.ddc | 510 | eng |
dc.subject.other | Non-intrusive | eng |
dc.subject.other | tensor reconstruction | eng |
dc.subject.other | partial differential equations with random coefficients | eng |
dc.subject.other | tensor representation | eng |
dc.subject.other | tensor train | eng |
dc.subject.other | uncertainty quantification | eng |
dc.subject.other | low-rank | eng |
dc.title | Non-intrusive tensor reconstruction for high dimensional random PDEs | eng |
dc.type | Report | eng |
dc.type | Text | eng |
tib.accessRights | openAccess | eng |
wgl.contributor | WIAS | eng |
wgl.subject | Mathematik | eng |
wgl.type | Report / Forschungsbericht / Arbeitspapier | eng |
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