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On the merits of sparse surrogates for global sensitivity analysis of multi-scale nonlinear problems: Application to turbulence and fire-spotting model in wildland fire simulators
16 references·0 citing·29 second hop
On the merits of sparse surrogates for global sensitivity analysis of multi-scale nonlinear problems: Application to turbulence and fire-spotting model in wildland fire simulators (2019)On the merits of sparse surrogates for gl…OpenTURNS: An Industrial Software for Uncertainty Quantification in Simulation (2017)OpenTURNS: An Industrial Soft…Introduction to Sensitivity Analysis (2017)Introduction to Sensitivity A…Handbook of Uncertainty Quantification (2016)Handbook of Uncertainty Quant…POLYNOMIAL-CHAOS-BASED KRIGING (2015)POLYNOMIAL-CHAOS-BASED KRIGINGMetamodel-Based Sensitivity Analysis: Polynomial Chaos Expansions and Gaussian Processes (2015)Metamodel-Based Sensitivity A…A Bayesian Approach for Global Sensitivity Analysis of (Multifidelity) Computer Codes (2014)A Bayesian Approach for Globa…Numerical Methods for Stochastic Computations: A Spectral Method Approach (2010)Numerical Methods for Stochas…Multivariate sensitivity analysis to measure global contribution of input factors in dynamic models (2010)Multivariate sensitivity anal…Adaptive sparse polynomial chaos expansion based on least angle regression (2010)Adaptive sparse polynomial ch…Implementation and evaluation of nonparametric regression procedures for sensitivity analysis of computationally demanding models (2009)Implementation and evaluation…Calculations of Sobol indices for the Gaussian process metamodel (2008)Calculations of Sobol indices…Introduction to Sensitivity Analysis (2007)Introduction to Sensitivity A…Global Sensitivity Analysis. The Primer (2007)Global Sensitivity Analysis. …Global sensitivity analysis using polynomial chaos expansions (2007)Global sensitivity analysis u…Probabilistic Sensitivity Analysis of Complex Models: A Bayesian Approach (2004)Probabilistic Sensitivity Ana…The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations (2002)The Wiener--Askey Polynomial …Stochastic Finite Elements: A Spectral Approach (1991)High-Order Collocation Methods for Differential Equations with Random Inputs (2005)A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (2000)Efficient computation of global sensitivity indices using sparse polynomial chaos expansions (2010)UQLab: A Framework for Uncertainty Quantification in Matlab (2014)A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output (1999)Design and Analysis of Computer Experiments (1989)STATISTICS FOR SPATIAL DATA (1992)Global Sensitivity Analysis for Systems with Independent and/or Correlated Inputs (2010)Mixed aleatory-epistemic uncertainty quantification with stochastic expansions and optimization-based interval estimation (2011)Asymptotic normality and efficiency of two Sobol index estimators (2013)Importance measures in global sensitivity analysis of nonlinear models (1996)A new uncertainty importance measure (2006)Bayesian analysis of computer code outputs: A tutorial (2006)How to avoid a perfunctory sensitivity analysis (2010)Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index (2009)Sensitivity analysis of environmental models: A systematic review with practical workflow (2016)SALib: An open-source Python library for Sensitivity Analysis (2017)Multilevel Monte Carlo methods and applications to elliptic PDEs with random coefficients (2011)Stochastic finite element methods for partial differential equations with random input data (2014)Chaospy: An open source tool for designing methods of uncertainty quantification (2015)Making sense of global sensitivity analyses (2013)Global sensitivity analysis with dependence measures (2014)An active-learning algorithm that combines sparse polynomial chaos expansions and bootstrap for structural reliability analysis (2018)Design and Analysis of Simulation Experiments (2018)Random forests for global sensitivity analysis: A selective review (2020)Rare Event Estimation Using Polynomial-Chaos Kriging (2016)Adaptive approaches in metamodel-based reliability analysis: A review (2020)Sparse Polynomial Chaos Expansions: Literature Survey and Benchmark (2021)
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References

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  • 2002The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations4,821 cited
  • 2007Global sensitivity analysis using polynomial chaos expansions2,547 cited
  • 2010Adaptive sparse polynomial chaos expansion based on least angle regression1,507 cited
  • 2010Numerical Methods for Stochastic Computations: A Spectral Method Approach1,107 cited
  • 2004Probabilistic Sensitivity Analysis of Complex Models: A Bayesian Approach1,085 cited
  • 2016Handbook of Uncertainty Quantification588 cited
  • 2015POLYNOMIAL-CHAOS-BASED KRIGING398 cited
  • 2008Calculations of Sobol indices for the Gaussian process metamodel331 cited
  • 2009Implementation and evaluation of nonparametric regression procedures for sensitivity analysis of computationally demanding models327 cited
  • 2010Multivariate sensitivity analysis to measure global contribution of input factors in dynamic models243 cited
  • 2007Introduction to Sensitivity Analysis178 cited
  • 2015Metamodel-Based Sensitivity Analysis: Polynomial Chaos Expansions and Gaussian Processes126 cited
  • 2017Introduction to Sensitivity Analysis125 cited
  • 2014A Bayesian Approach for Global Sensitivity Analysis of (Multifidelity) Computer Codes

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105 cited
  • 2017OpenTURNS: An Industrial Software for Uncertainty Quantification in Simulation91 cited
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