Compressive Sampling Methods for Sparse Polynomial Chaos Expansions

Handbook of Uncertainty Quantification ◽

10.1007/978-3-319-11259-6_67-1 ◽

2015 ◽

pp. 1-29 ◽

Cited By ~ 3

Author(s):

Jerrad Hampton ◽

Alireza Doostan

Keyword(s):

Polynomial Chaos ◽

Sampling Methods ◽

Compressive Sampling ◽

Sparse Polynomial ◽

Polynomial Chaos Expansions

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Compressive Sampling Methods for Sparse Polynomial Chaos Expansions

Handbook of Uncertainty Quantification ◽

10.1007/978-3-319-12385-1_67 ◽

2017 ◽

pp. 827-855 ◽

Cited By ~ 1

Author(s):

Jerrad Hampton ◽

Alireza Doostan

Keyword(s):

Polynomial Chaos ◽

Sampling Methods ◽

Compressive Sampling ◽

Sparse Polynomial ◽

Polynomial Chaos Expansions

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A preconditioning approach for improved estimation of sparse polynomial chaos expansions

Computer Methods in Applied Mechanics and Engineering ◽

10.1016/j.cma.2018.08.005 ◽

2018 ◽

Vol 342 ◽

pp. 474-489 ◽

Cited By ~ 2

Author(s):

Negin Alemazkoor ◽

Hadi Meidani

Keyword(s):

Polynomial Chaos ◽

Sparse Polynomial ◽

Polynomial Chaos Expansions

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Efficient computation of global sensitivity indices using sparse polynomial chaos expansions

Reliability Engineering & System Safety ◽

10.1016/j.ress.2010.06.015 ◽

2010 ◽

Vol 95 (11) ◽

pp. 1216-1229 ◽

Cited By ~ 190

Author(s):

Géraud Blatman ◽

Bruno Sudret

Keyword(s):

Polynomial Chaos ◽

Efficient Computation ◽

Global Sensitivity ◽

Sparse Polynomial ◽

Sensitivity Indices ◽

Polynomial Chaos Expansions

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Uncertainty Study of Periodic-Grating Wideband Filters With Sparse Polynomial-Chaos Expansions

IEEE Photonics Technology Letters ◽

10.1109/lpt.2019.2935322 ◽

2019 ◽

Vol 31 (18) ◽

pp. 1499-1502

Author(s):

A. D. Papadopoulos ◽

T. T. Zygiridis ◽

E. N. Glytsis ◽

N. V. Kantartzis ◽

C. S. Antonopoulos

Keyword(s):

Polynomial Chaos ◽

Sparse Polynomial ◽

Periodic Grating ◽

Polynomial Chaos Expansions ◽

Wideband Filters

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THE UPLIFT CAPACITY OF HORIZONTAL PLATE ANCHORS IN SPATIALLY VARIABLE CLAY USING SPARSE POLYNOMIAL CHAOS EXPANSIONS

Proceedings of the VII European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS Congress 2016) ◽

10.7712/100016.2448.7622 ◽

2016 ◽

Author(s):

Tom Charlton ◽

Mohamed Rouainia

Keyword(s):

Polynomial Chaos ◽

Uplift Capacity ◽

Horizontal Plate ◽

Sparse Polynomial ◽

Plate Anchors ◽

Polynomial Chaos Expansions

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Using sparse polynomial chaos expansions for the global sensitivity analysis of groundwater lifetime expectancy in a multi-layered hydrogeological model

Reliability Engineering & System Safety ◽

10.1016/j.ress.2015.11.005 ◽

2016 ◽

Vol 147 ◽

pp. 156-169 ◽

Cited By ~ 37

Author(s):

G. Deman ◽

K. Konakli ◽

B. Sudret ◽

J. Kerrou ◽

P. Perrochet ◽

...

Keyword(s):

Sensitivity Analysis ◽

Polynomial Chaos ◽

Global Sensitivity Analysis ◽

Hydrogeological Model ◽

Global Sensitivity ◽

Sparse Polynomial ◽

Polynomial Chaos Expansions ◽

Lifetime Expectancy

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An adaptive algorithm to build up sparse polynomial chaos expansions for stochastic finite element analysis

Probabilistic Engineering Mechanics ◽

10.1016/j.probengmech.2009.10.003 ◽

2010 ◽

Vol 25 (2) ◽

pp. 183-197 ◽

Cited By ~ 377

Author(s):

Géraud Blatman ◽

Bruno Sudret

Keyword(s):

Finite Element Analysis ◽

Finite Element ◽

Adaptive Algorithm ◽

Polynomial Chaos ◽

Stochastic Finite Element ◽

Element Analysis ◽

Sparse Polynomial ◽

Stochastic Finite Element Analysis ◽

Polynomial Chaos Expansions

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Sliced inverse regression-based sparse polynomial chaos expansions for reliability analysis in high dimensions

Reliability Engineering & System Safety ◽

10.1016/j.ress.2017.06.026 ◽

2017 ◽

Vol 167 ◽

pp. 484-493 ◽

Cited By ~ 37

Author(s):

Qiujing Pan ◽

Daniel Dias

Keyword(s):

Reliability Analysis ◽

Polynomial Chaos ◽

Sliced Inverse Regression ◽

Inverse Regression ◽

High Dimensions ◽

Sparse Polynomial ◽

Polynomial Chaos Expansions

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Automatic selection of basis-adaptive sparse polynomial chaos expansions for engineering applications

International Journal for Uncertainty Quantification ◽

10.1615/int.j.uncertaintyquantification.2021036153 ◽

2021 ◽

Author(s):

Nora Lüthen ◽

Stefano Marelli ◽

Bruno Sudret

Keyword(s):

Polynomial Chaos ◽

Engineering Applications ◽

Sparse Polynomial ◽

Automatic Selection ◽

Polynomial Chaos Expansions ◽

Selection Of

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Global sensitivity analysis in the context of imprecise probabilities (p-boxes) using sparse polynomial chaos expansions

Reliability Engineering & System Safety ◽

10.1016/j.ress.2018.11.021 ◽

2019 ◽

Vol 187 ◽

pp. 129-141 ◽

Cited By ~ 11

Author(s):

Roland Schöbi ◽

Bruno Sudret

Keyword(s):

Sensitivity Analysis ◽

Polynomial Chaos ◽

Global Sensitivity Analysis ◽

Imprecise Probabilities ◽

Global Sensitivity ◽

Sparse Polynomial ◽

Polynomial Chaos Expansions

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