Tensor completion for PDEs with uncertain coefficients and Bayesian Update

Handle URI:
http://hdl.handle.net/10754/623695
Title:
Tensor completion for PDEs with uncertain coefficients and Bayesian Update
Authors:
Litvinenko, Alexander ( 0000-0001-5427-3598 )
Abstract:
In this work, we tried to show connections between Bayesian update and tensor completion techniques. Usually, only a small/sparse vector/tensor of measurements is available. The typical measurement is a function of the solution. The solution of a stochastic PDE is a tensor, the measurement as well. The idea is to use completion techniques to compute all "missing" values of the measurement tensor and only then apply the Bayesian technique.
KAUST Department:
Extreme Computing Research Center; SRI Center for Uncertainty Quantification in Computational Science and Engineering, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
Conference/Event name:
SIAM CSE Conference
Issue Date:
5-Mar-2017
Type:
Presentation
Sponsors:
ECRC KAUST, SRI UQ KAUST
Additional Links:
http://meetings.siam.org/sess/dsp_programsess.cfm?SESSIONCODE=61237
Appears in Collections:
Presentations

Full metadata record

DC FieldValue Language
dc.contributor.authorLitvinenko, Alexanderen
dc.date.accessioned2017-05-23T06:13:09Z-
dc.date.available2017-05-23T06:13:09Z-
dc.date.issued2017-03-05-
dc.identifier.urihttp://hdl.handle.net/10754/623695-
dc.description.abstractIn this work, we tried to show connections between Bayesian update and tensor completion techniques. Usually, only a small/sparse vector/tensor of measurements is available. The typical measurement is a function of the solution. The solution of a stochastic PDE is a tensor, the measurement as well. The idea is to use completion techniques to compute all "missing" values of the measurement tensor and only then apply the Bayesian technique.en
dc.description.sponsorshipECRC KAUST, SRI UQ KAUSTen
dc.relation.urlhttp://meetings.siam.org/sess/dsp_programsess.cfm?SESSIONCODE=61237en
dc.subjectBayesian inferenceen
dc.subjectBayesian updateen
dc.subjectposterioren
dc.subjectmissing dataen
dc.subjectcompletion techniquesen
dc.subjectlow-rank tensorsen
dc.titleTensor completion for PDEs with uncertain coefficients and Bayesian Updateen
dc.typePresentationen
dc.contributor.departmentExtreme Computing Research Centeren
dc.contributor.departmentSRI Center for Uncertainty Quantification in Computational Science and Engineering, King Abdullah University of Science and Technology, Thuwal, Saudi Arabiaen
dc.conference.dateMarch 2017en
dc.conference.nameSIAM CSE Conferenceen
dc.conference.locationAtlanta , USAen
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