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Global sensitivity analysis in the context of imprecise probabilities (p-boxes) using sparse polynomial chaos expansions
16 references·16 citing·25 second hopsampled
Global sensitivity analysis in the context of imprecise probabilities (p-boxes) using sparse polynomial chaos expansions (2018)Global sensitivity analysis in the contex…UQLab: A Framework for Uncertainty Quantification in Matlab (2014)UQLab: A Framework for Uncert…A combined Importance Sampling and Kriging reliability method for small failure probabilities with time-demanding numerical models (2012)A combined Importance Samplin…AK-MCS: An active learning reliability method combining Kriging and Monte Carlo Simulation (2011)AK-MCS: An active learning re…Adaptive sparse polynomial chaos expansion based on least angle regression (2010)Adaptive sparse polynomial ch…An adaptive algorithm to build up sparse polynomial chaos expansions for stochastic finite element analysis (2009)An adaptive algorithm to buil…Aleatory or epistemic? Does it matter? (2008)Aleatory or epistemic? Does i…Global Sensitivity Analysis. The Primer (2007)Global Sensitivity Analysis. …Global sensitivity analysis using polynomial chaos expansions (2007)Global sensitivity analysis u…Survey of sampling-based methods for uncertainty and sensitivity analysis (2006)Survey of sampling-based meth…The Design and Analysis of Computer Experiments (2003)The Design and Analysis of Co…Constructing Probability Boxes and Dempster-Shafer Structures (2003)Constructing Probability Boxe…The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations (2002)The Wiener--Askey Polynomial …Importance measures in global sensitivity analysis of nonlinear models (1996)Importance measures in global…Different methods are needed to propagate ignorance and variability (1996)Different methods are needed …Stochastic Finite Elements: A Spectral Approach (1991)Stochastic Finite Elements: A…Design and Analysis of Computer Experiments (1989)Design and Analysis of Comput…Partial gradient-enhanced multi-output sparse polynomial chaos expansion method for model representation (2025)Partial gradient-enhanced mul…Extreme-oriented sensitivity analysis using sparse polynomial chaos expansion. Application to train–track–bridge systems (2023)Extreme-oriented sensitivity …Global Sensitivity Analysis Using a Kriging Metamodel for EM Design Problems With Functional Outputs (2022)Global Sensitivity Analysis U…Differentiating effects of input aleatory and epistemic uncertainties on system output: A separating sensitivity analysis approach (2022)Differentiating effects of in…Deep adaptive arbitrary polynomial chaos expansion: A mini-data-driven semi-supervised method for uncertainty quantification (2022)Deep adaptive arbitrary polyn…Consistency regularization-based deep polynomial chaos neural network method for reliability analysis (2022)Consistency regularization-ba…Reliability-oriented sensitivity analysis in presence of data-driven epistemic uncertainty (2021)Reliability-oriented sensitiv…Efficient imprecise reliability analysis using the Augmented Space Integral (2021)Efficient imprecise reliabili…Imprecise random field analysis for non-linear concrete damage analysis (2020)Imprecise random field analys…Imprecise global sensitivity analysis using bayesian multimodel inference and importance sampling (2020)Imprecise global sensitivity …Efficient uncertainty propagation for parameterized p-box using sparse-decomposition-based polynomial chaos expansion (2020)Efficient uncertainty propaga…Bounding the first excursion probability of linear structures subjected to imprecise stochastic loading (2020)Bounding the first excursion …An efficient method based on AK-MCS for estimating failure probability function (2020)An efficient method based on …A general frame for uncertainty propagation under multimodally distributed random variables (2020)A general frame for uncertain…Regression-based sparse polynomial chaos for uncertainty quantification of subsurface flow models (2019)Regression-based sparse polyn…A framework for global reliability sensitivity analysis in the presence of multi-uncertainty (2019)A framework for global reliab…Structural Reliability Methods (1996)Kriging metamodeling in simulation: A review (2007)Metamodel-based importance sampling for structural reliability analysis (2013)LIF: A new Kriging based learning function and its application to structural reliability analysis (2016)Statistics for Experimenters (1979)A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (2000)Handbook on Constructing Composite Indicators (2005)An effective screening design for sensitivity analysis of large models (2007)A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output (1999)The Logic of Scientific Discovery. (1960)Logic of Scientific Discovery, The (2010)Reliability-based design optimization using kriging surrogates and subset simulation (2011)Imprecise probabilities in engineering analyses (2013)Variable importance analysis: A comprehensive review (2015)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)Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems (2003)Taking the Human Out of the Loop: A Review of Bayesian Optimization (2015)High-Order Collocation Methods for Differential Equations with Random Inputs (2005)Efficient computation of global sensitivity indices using sparse polynomial chaos expansions (2010)POLYNOMIAL-CHAOS-BASED KRIGING (2015)An Explicit Link between Gaussian Fields and Gaussian Markov Random Fields: The Stochastic Partial Differential Equation Approach (2011)A Review on Global Sensitivity Analysis Methods (2015)Sensitivity analysis: A review of recent advances (2015)
this work references cited by second hop· second hop is a sample of the most-cited connections

References

  • 1989Design and Analysis of Computer Experiments6,958 cited
  • 2007Global Sensitivity Analysis. The Primer6,425 cited
  • 1991Stochastic Finite Elements: A Spectral Approach5,753 cited
  • 2002The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations4,821 cited
  • 2007Global sensitivity analysis using polynomial chaos expansions2,547 cited
  • 2008Aleatory or epistemic? Does it matter?2,450 cited
  • 2003The Design and Analysis of Computer Experiments2,204 cited
  • 2011AK-MCS: An active learning reliability method combining Kriging and Monte Carlo Simulation2,048 cited
  • 1996Importance measures in global sensitivity analysis of nonlinear models2,014 cited
  • 2010Adaptive sparse polynomial chaos expansion based on least angle regression1,507 cited
  • 2006Survey of sampling-based methods for uncertainty and sensitivity analysis1,240 cited
  • 2014UQLab: A Framework for Uncertainty Quantification in Matlab1,018 cited
  • 2009An adaptive algorithm to build up sparse polynomial chaos expansions for stochastic finite element analysis834 cited
  • 2003Constructing Probability Boxes and Dempster-Shafer Structures745 cited
  • 2012A combined Importance Sampling and Kriging reliability method for small failure probabilities with time-demanding numerical models

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692 cited
  • 1996Different methods are needed to propagate ignorance and variability621 cited
  • Cited by

    • 2020A general frame for uncertainty propagation under multimodally distributed random variables54 cited
    • 2020An efficient method based on AK-MCS for estimating failure probability function51 cited
    • 2020Bounding the first excursion probability of linear structures subjected to imprecise stochastic loading49 cited
    • 2022Deep adaptive arbitrary polynomial chaos expansion: A mini-data-driven semi-supervised method for uncertainty quantification44 cited
    • 2020Efficient uncertainty propagation for parameterized p-box using sparse-decomposition-based polynomial chaos expansion43 cited
    • 2021Reliability-oriented sensitivity analysis in presence of data-driven epistemic uncertainty38 cited
    • 2021Efficient imprecise reliability analysis using the Augmented Space Integral34 cited
    • 2023Extreme-oriented sensitivity analysis using sparse polynomial chaos expansion. Application to train–track–bridge systems30 cited
    • 2022Consistency regularization-based deep polynomial chaos neural network method for reliability analysis30 cited
    • 2020Imprecise global sensitivity analysis using bayesian multimodel inference and importance sampling28 cited
    • 2019A framework for global reliability sensitivity analysis in the presence of multi-uncertainty27 cited
    • 2025Partial gradient-enhanced multi-output sparse polynomial chaos expansion method for model representation26 cited
    • 2019Regression-based sparse polynomial chaos for uncertainty quantification of subsurface flow models26 cited
    • 2022Differentiating effects of input aleatory and epistemic uncertainties on system output: A separating sensitivity analysis approach24 cited
    • 2022Global Sensitivity Analysis Using a Kriging Metamodel for EM Design Problems With Functional Outputs21 cited
    • 2020Imprecise random field analysis for non-linear concrete damage analysis21 cited