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ArticleGlobal sensitivity analysis using low-rank tensor approximations

Katerina Konakli2016

OA

Articlegreen2016

Global sensitivity analysis using low-rank tensor approximations

Katerina Konakli · Bruno Sudret

95 citations·0/0 files stored·Reliability Engineering & System Safety

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Probabilistic and Robust Engineering Design Advanced Multi-Objective Optimization Algorithms Gaussian Processes and Bayesian Inference

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References

2007Global Sensitivity Analysis. The Primer 2001Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates 1991Factorial Sampling Plans for Preliminary Computational Experiments 2002The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations 2009Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index 2007Global sensitivity analysis using polynomial chaos expansions 1999A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output 2002Making best use of model evaluations to compute sensitivity indices

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2017Sequential Design of Experiment for Sparse Polynomial Chaos Expansions 2024A Review of Recent Advances in Surrogate Models for Uncertainty Quantification of High-Dimensional Engineering Applications 2022An efficient multi-fidelity Kriging surrogate model-based method for global sensitivity analysis 2018Global sensitivity analysis in the context of imprecise probabilities (p-boxes) using sparse polynomial chaos expansions 2023

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Details

Year2016

Typearticle

Published2016-07-17

VenueReliability Engineering & System Safety

ISSN-L0951-8320

Languageen

Citations95

Files0 public / 0

ShelfProbabilistic and Robust Engineering Design

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doi10.1016/j.ress.2016.07.012

openalex_workW2416632929

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