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Predictive Computational Science: Computer Predictions in the Presence of Uncertainty
10 references·3 citing·42 second hop
Predictive Computational Science: Computer Predictions in the Presence of Uncertainty (2017)Predictive Computational Science: Compute…Optimal Uncertainty Quantification (2013)Optimal Uncertainty Quantific…The Parallel C++ Statistical Library ‘QUESO’: Quantification of Uncertainty for Estimation, Simulation and Optimization (2012)The Parallel C++ Statistical …PRIOR AND POSTERIOR ROBUST STOCHASTIC PREDICTIONS FOR DYNAMICAL SYSTEMS USING PROBABILITY LOGIC (2012)PRIOR AND POSTERIOR ROBUST ST…Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index (2009)Variance based sensitivity an…A systematic approach to model validation based on Bayesian updates and prediction related rejection criteria (2008)A systematic approach to mode…A Framework for Validation of Computer Models (2007)A Framework for Validation of…Making best use of model evaluations to compute sensitivity indices (2002)Making best use of model eval…Importance measures in global sensitivity analysis of nonlinear models (1996)Importance measures in global…About the use of rank transformation in sensitivity analysis of model output (1995)About the use of rank transfo…Study of the sensitivity of coupled reaction systems to uncertainties in rate coefficients. I Theory (1973)Study of the sensitivity of c…A predictive multiphase model of silica aerogels for building envelope insulations (2022)A predictive multiphase model…Bayesian modeling of inconsistent plastic response due to material variability (2019)Bayesian modeling of inconsis…Verification and Validation in Fluids Engineering: Some Current Issues (2016)Verification and Validation i…A Difficulty in the Concept of Social Welfare (1950)Manipulation of Voting Schemes: A General Result (1973)Strategy-proofness and Arrow's conditions: Existence and correspondence theorems for voting procedures and social welfare functions (1975)Building a Framework for Predictive Science (2011)A distributionally robust perspective on uncertainty quantification and chance constrained programming (2015)Ambiguous Joint Chance Constraints Under Mean and Dispersion Information (2017)Estimation of small failure probabilities in high dimensions by subset simulation (2001)An efficient framework for optimal robust stochastic system design using stochastic simulation (2008)Sequential approximate optimization for design under uncertainty problems utilizing Kriging metamodeling in augmented input space (2016)Adaptive Kriging Stochastic Sampling and Density Approximation and Its Application to Rare-Event Estimation (2018)Adaptive multiscale predictive modelling (2018)Statistics for Experimenters (1979)Design and Analysis of Computer Experiments (1989)Factorial Sampling Plans for Preliminary Computational Experiments (1991)Sensitivity analysis of model output (1997)Random balance designs for the estimation of first order global sensitivity indices (2005)Convergence and uncertainty analyses in Monte-Carlo based sensitivity analysis (2010)Stochastic Calculus: Applications in Science and Engineering (2002)Bayesian inference of random fields represented with the Karhunen–Loève expansion (2019)Unified Framework and Survey for Model Verification, Validation and Uncertainty Quantification (2020)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)Sensitivity analysis of environmental models: A systematic review with practical workflow (2016)Verification, Validation, and Confirmation of Numerical Models in the Earth Sciences (1994)Calibration, validation, and sensitivity analysis: What's what (2006)Measures of agreement between computation and experiment: Validation metrics (2006)Quantification of Model Uncertainty: Calibration, Model Discrepancy, and Identifiability (2012)A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output (1999)Global sensitivity analysis using polynomial chaos expansions (2007)Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates (2001)Global Sensitivity Analysis. The Primer (2007)How to avoid a perfunctory sensitivity analysis (2010)SALib: An open-source Python library for Sensitivity Analysis (2017)A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data (2007)A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data (2010)DAKOTA : a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis. Version 5.0, user's manual. (2010)Bayesian experimental design for the active nitridation of graphite by atomic nitrogen (2011)A computational framework for dynamic data‐driven material damage control, based on Bayesian inference and model selection (2014)Identification and Review of Sensitivity Analysis Methods (2002)Probabilistic Sensitivity Analysis of Complex Models: A Bayesian Approach (2004)Model-based design of experiments for parameter precision: State of the art (2007)
this work references cited by second hop

References

  • 2009Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index3,567 cited
  • 2002Making best use of model evaluations to compute sensitivity indices2,225 cited
  • 1996Importance measures in global sensitivity analysis of nonlinear models2,014 cited
  • 1973Study of the sensitivity of coupled reaction systems to uncertainties in rate coefficients. I Theory1,041 cited
  • 2007A Framework for Validation of Computer Models656 cited
  • 1995About the use of rank transformation in sensitivity analysis of model output340 cited
  • 2013Optimal Uncertainty Quantification129 cited
  • 2008A systematic approach to model validation based on Bayesian updates and prediction related rejection criteria76 cited
  • 2012PRIOR AND POSTERIOR ROBUST STOCHASTIC PREDICTIONS FOR DYNAMICAL SYSTEMS USING PROBABILITY LOGIC72 cited
  • 2012The Parallel C++ Statistical Library ‘QUESO’: Quantification of Uncertainty for Estimation, Simulation and Optimization69 cited

Cited by

  • 2016Verification and Validation in Fluids Engineering: Some Current Issues19 cited
  • 2019Bayesian modeling of inconsistent plastic response due to material variability15 cited
  • 2022A predictive multiphase model of silica aerogels for building envelope insulations10 cited

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