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Sequential Refinement of Uncertainty Through Bayesian Inference and Global Sensitivity Analysis
16 references·1 citing·44 second hop
Sequential Refinement of Uncertainty Through Bayesian Inference and Global Sensitivity Analysis (2015)Sequential Refinement of Uncertainty Thro…Likelihood-based representation of epistemic uncertainty due to sparse point data and/or interval data (2011)Likelihood-based representati…Bayesian Network Enhanced with Structural Reliability Methods: Methodology (2010)Bayesian Network Enhanced wit…Aleatory or epistemic? Does it matter? (2008)Aleatory or epistemic? Does i…Global Sensitivity Analysis. The Primer (2007)Global Sensitivity Analysis. …Experimental uncertainty estimation and statistics for data having interval uncertainty. (2007)Experimental uncertainty esti…Estimating the approximation error when fixing unessential factors in global sensitivity analysis (2006)Estimating the approximation …Uncertainty quantification using evidence theory in multidisciplinary design optimization (2004)Uncertainty quantification us…Challenge problems: uncertainty in system response given uncertain parameters (2004)Challenge problems: uncertain…An exploration of alternative approaches to the representation of uncertainty in model predictions (2004)An exploration of alternative…An exploration of alternative approaches to the representation of uncertainty in model predictions (2004)An exploration of alternative…An approximation approach for uncertainty quantification using evidence theory (2004)An approximation approach for…Probability, reliability and statistical methods in engineering design (1999)Probability, reliability and …Different methods are needed to propagate ignorance and variability (1996)Different methods are needed …Global Sensitivity Analysis (1995)Global Sensitivity AnalysisA non-probabilistic measure of reliability of linear systems based on expansion of convex models (1995)A non-probabilistic measure o…Convex Models of Uncertainty in Applied Mechanics (1990)Convex Models of Uncertainty …Framework for Quantification and Risk Analysis for Layered Uncertainty using Optimization: NASA UQ Challenge (2014)Framework for Quantification …Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates (2001)Making best use of model evaluations to compute sensitivity indices (2002)Sensitivity Analysis in Practice (2002)Estimation of global sensitivity indices for models with dependent variables (2011)Sobol' Indices and Shapley Value (2014)A guide to uncertainty quantification and sensitivity analysis for cardiovascular applications (2015)Principles of Operations Research. 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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)Antioptimization of structures with large uncertain-but-non-random parameters via interval analysis (1998)Galerkin Finite Element Approximations of Stochastic Elliptic Partial Differential Equations (2004)Review of uncertainty-based multidisciplinary design optimization methods for aerospace vehicles (2011)Efficient Global Reliability Analysis for Nonlinear Implicit Performance Functions (2008)DAKOTA : a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis. Version 5.0, user's manual. (2010)
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References

  • 2007Global Sensitivity Analysis. The Primer6,425 cited
  • 2008Aleatory or epistemic? Does it matter?2,450 cited
  • 1999Probability, reliability and statistical methods in engineering design1,377 cited
  • 1995Global Sensitivity Analysis931 cited
  • 1990Convex Models of Uncertainty in Applied Mechanics838 cited
  • 1996Different methods are needed to propagate ignorance and variability621 cited
  • 2004Challenge problems: uncertainty in system response given uncertain parameters570 cited
  • 2006Estimating the approximation error when fixing unessential factors in global sensitivity analysis395 cited
  • 2004An exploration of alternative approaches to the representation of uncertainty in model predictions362 cited
  • 2004Uncertainty quantification using evidence theory in multidisciplinary design optimization324 cited
  • 2004An exploration of alternative approaches to the representation of uncertainty in model predictions284 cited
  • 2007Experimental uncertainty estimation and statistics for data having interval uncertainty.219 cited
  • 2004An approximation approach for uncertainty quantification using evidence theory197 cited
  • 2010Bayesian Network Enhanced with Structural Reliability Methods: Methodology182 cited
  • 1995

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A non-probabilistic measure of reliability of linear systems based on expansion of convex models
163 cited
  • 2011Likelihood-based representation of epistemic uncertainty due to sparse point data and/or interval data156 cited
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    • 2014Framework for Quantification and Risk Analysis for Layered Uncertainty using Optimization: NASA UQ Challenge5 cited