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Polynomial meta-models with canonical low-rank approximations: numerical
  insights and comparison to sparse polynomial chaos expansions

Polynomial meta-models with canonical low-rank approximations: numerical insights and comparison to sparse polynomial chaos expansions

23 November 2015
K. Konakli
Bruno Sudret
ArXivPDFHTML

Papers citing "Polynomial meta-models with canonical low-rank approximations: numerical insights and comparison to sparse polynomial chaos expansions"

2 / 2 papers shown
Title
Global sensitivity analysis using low-rank tensor approximations
Global sensitivity analysis using low-rank tensor approximations
K. Konakli
Bruno Sudret
34
77
0
29 May 2016
A least-squares method for sparse low rank approximation of multivariate
  functions
A least-squares method for sparse low rank approximation of multivariate functions
M. Chevreuil
R. Lebrun
A. Nouy
Prashant Rai
50
103
0
30 Apr 2013
1