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GLOBAL SENSITIVITY ANALYSIS OF RARE EVENT PROBABILITIES USING SUBSET SIMULATION AND POLYNOMIAL CHAOS EXPANSIONS
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GLOBAL SENSITIVITY ANALYSIS OF RARE EVENT PROBABILITIES USING SUBSET SIMULATION AND POLYNOMIAL CHAOS EXPANSIONS (2022)GLOBAL SENSITIVITY ANALYSIS OF RARE EVENT…Structural Reliability Analysis and Prediction (2017)Structural Reliability Analys…Rare-event probability estimation with adaptive support vector regression surrogates (2016)Rare-event probability estima…MCMC algorithms for Subset Simulation (2015)MCMC algorithms for Subset Si…A Review on Global Sensitivity Analysis Methods (2015)A Review on Global Sensitivit…Efficient surrogate models for reliability analysis of systems with multiple failure modes (2011)Efficient surrogate models fo…Bayesian post-processor and other enhancements of Subset Simulation for estimating failure probabilities in high dimensions (2011)Bayesian post-processor and o…Spectral Methods for Uncertainty Quantification (2010)Spectral Methods for Uncertai…Spectral methods for uncertainty quantification : with applications to computational fluid dynamics (2010)Spectral methods for uncertai…Efficient computation of global sensitivity indices using sparse polynomial chaos expansions (2010)Efficient computation of glob…Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index (2009)Variance based sensitivity an…Polynomial chaos expansion for sensitivity analysis (2008)Polynomial chaos expansion fo…Stochastic Simulation (2007)Stochastic SimulationGlobal Sensitivity Analysis. The Primer (2007)Global Sensitivity Analysis. …A critical appraisal of reliability estimation procedures for high dimensions (2004)A critical appraisal of relia…Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates (2001)Global sensitivity indices fo…Estimation of small failure probabilities in high dimensions by subset simulation (2001)Estimation of small failure p…Design and Analysis of Computer Experiments (1989)A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (2000)Random forests for global sensitivity analysis: A selective review (2020)The Future of Sensitivity Analysis: An essential discipline for systems modeling and policy support (2020)A Survey on High-dimensional Gaussian Process Modeling with Application to Bayesian Optimization (2022)Simulation and the Monte Carlo Method (1981)The stochastic finite element method: Past, present and future (2008)A combined Importance Sampling and Kriging reliability method for small failure probabilities with time-demanding numerical models (2012)The generalization of Latin hypercube sampling (2015)Simulation and the Monte Carlo Method (2016)Stochastic Finite Elements: A Spectral Approach (1991)The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations (2002)Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems (2003)Data-driven uncertainty quantification using the arbitrary polynomial chaos expansion (2012)Stochastic analysis of the fracture toughness of polymeric nanoparticle composites using polynomial chaos expansions (2017)Sensitivity and uncertainty analysis for flexoelectric nanostructures (2018)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)An Introduction to Computational Stochastic PDEs (2014)Modern Monte Carlo methods for efficient uncertainty quantification and propagation: A survey (2020)Uncertainties in risk analysis: Six levels of treatment (1996)Reliability analysis—a review and some perspectives (2001)Sequential Optimization and Reliability Assessment Method for Efficient Probabilistic Design (2004)Simulation-based optimal Bayesian experimental design for nonlinear systems (2012)Compressive sampling of polynomial chaos expansions: Convergence analysis and sampling strategies (2014)Stochastic finite element methods for partial differential equations with random input data (2014)How to avoid a perfunctory sensitivity analysis (2010)A new uncertainty importance measure (2006)A Guide to Sample Average Approximation (2014)Simulation Modeling and Analysis (2016)A unified framework for stochastic optimization (2018)
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References

  • 2007Global Sensitivity Analysis. The Primer6,425 cited
  • 2001Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates6,377 cited
  • 2017Structural Reliability Analysis and Prediction3,780 cited
  • 2009Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index3,567 cited
  • 2001Estimation of small failure probabilities in high dimensions by subset simulation2,419 cited
  • 2007Stochastic Simulation1,121 cited
  • 2015A Review on Global Sensitivity Analysis Methods1,113 cited
  • 2010Spectral Methods for Uncertainty Quantification953 cited
  • 2008Polynomial chaos expansion for sensitivity analysis747 cited
  • 2010Spectral methods for uncertainty quantification : with applications to computational fluid dynamics572 cited
  • 2004A critical appraisal of reliability estimation procedures for high dimensions476 cited
  • 2015MCMC algorithms for Subset Simulation413 cited
  • 2010Efficient computation of global sensitivity indices using sparse polynomial chaos expansions383 cited
  • 2011Efficient surrogate models for reliability analysis of systems with multiple failure modes290 cited
  • 2011Bayesian post-processor and other enhancements of Subset Simulation for estimating failure probabilities in high dimensions

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213 cited
  • 2016Rare-event probability estimation with adaptive support vector regression surrogates210 cited
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