Uncertainty Quantification - an Overview

Handle URI:
http://hdl.handle.net/10754/627222
Title:
Uncertainty Quantification - an Overview
Authors:
Litvinenko, Alexander ( 0000-0001-5427-3598 )
Abstract:
1. Introduction to UQ 2. Low-rank tensors for representation of big/high-dimensional data 3. Inverse Problem via Bayesian Update 4. R-INLA and advance numerics for spatio-temporal statistics 5. High Performance Computing, parallel algorithms
KAUST Department:
Bayesian computational statistics, CEMSE
Conference/Event name:
invited talk, Durham University, UK
Issue Date:
1-Mar-2018
Type:
Presentation
Appears in Collections:
Presentations

Full metadata record

DC FieldValue Language
dc.contributor.authorLitvinenko, Alexanderen
dc.date.accessioned2018-03-05T12:17:14Z-
dc.date.available2018-03-05T12:17:14Z-
dc.date.issued2018-03-01-
dc.identifier.urihttp://hdl.handle.net/10754/627222-
dc.description.abstract1. Introduction to UQ 2. Low-rank tensors for representation of big/high-dimensional data 3. Inverse Problem via Bayesian Update 4. R-INLA and advance numerics for spatio-temporal statistics 5. High Performance Computing, parallel algorithmsen
dc.subjectLow-rank tensorsen
dc.subjectUncertainty Quantificationen
dc.subjectParallel Computingen
dc.subjectH-matricesen
dc.subjectBayesian surrogateen
dc.titleUncertainty Quantification - an Overviewen
dc.typePresentationen
dc.contributor.departmentBayesian computational statistics, CEMSEen
dc.conference.date1 March, 2018en
dc.conference.nameinvited talk, Durham University, UKen
dc.conference.locationDurham University, UKen
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