Efficient low-rank approximation of the stochastic Galerkin matrix in tensor formats

Computers and Mathematics with Applications

Volumn 67, Issue 4, 2014, Pages 818-829

  Espig, Mike ^a   Hackbusch, Wolfgang ^a   Litvinenko, Alexander ^b   Matthies, Hermann G ^b   Wähnert, Philipp ^a  

^a MAX PLANCK INSTITUTE FOR MATHEMATICS IN THE SCIENCES   (Germany)

^b TECHNICAL UNIVERSITY OF BRAUNSCHWEIG   (Germany)

Author keywords

Low rank tensor formats; Stochastic Galerkin matrix; Stochastic PDEs; Tensor approximation; Uncertainty quantification

Indexed keywords

APPROXIMATION ERRORS; HIERARCHICAL TENSORS; LOW RANK APPROXIMATIONS; LOW-RANK TENSOR FORMATS; MULTIVARIATE HERMITE POLYNOMIALS; STOCHASTIC PDES; TENSOR APPROXIMATION; UNCERTAINTY QUANTIFICATIONS;

GALERKIN METHODS; POLYNOMIALS; STOCHASTIC SYSTEMS;

TENSORS;

EID: 84893873908     PISSN: 08981221     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.camwa.2012.10.008     Document Type: Article

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