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Integrating Bayesian Calibration, Bias Correction, and Machine Learning for the 2014 Sandia Verification and Validation Challenge Problem
16 references·9 citing·33 second hop
Integrating Bayesian Calibration, Bias Correction, and Machine Learning for the 2014 Sandia Verification and Validation Challenge Problem (2015)Integrating Bayesian Calibration, Bias Co…New validation metrics for models with multiple correlated responses (2014)New validation metrics for mo…Reliability-Based Design Optimization with Model Bias and Data Uncertainty (2013)Reliability-Based Design Opti…Quantification of Model Uncertainty: Calibration, Model Discrepancy, and Identifiability (2012)Quantification of Model Uncer…Improving Identifiability in Model Calibration Using Multiple Responses (2012)Improving Identifiability in …Toward a Better Understanding of Model Validation Metrics (2011)Toward a Better Understanding…A comprehensive framework for verification, validation, and uncertainty quantification in scientific computing (2011)A comprehensive framework for…Guide for Verification and Validation in Computational Solid Mechanics (2009)Guide for Verification and Va…A comparative study of uncertainty propagation methods for black-box-type problems (2008)A comparative study of uncert…Model validation and predictive capability for the thermal challenge problem (2007)Model validation and predicti…A Framework for Validation of Computer Models (2007)A Framework for Validation of…A Design-Driven Validation Approach Using Bayesian Prediction Models (2007)A Design-Driven Validation Ap…Measures of agreement between computation and experiment: Validation metrics (2006)Measures of agreement between…Understanding the Effects of Model Uncertainty in Robust Design With Computer Experiments (2005)Understanding the Effects of …Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates (2001)Global sensitivity indices fo…A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output (1999)A Quantitative Model-Independ…Empirical Model Building and Response Surfaces (1988)Empirical Model Building and …Probabilistic Validation: Theoretical Foundation and Methodological Platform (2023)Probabilistic Validation: The…A modular Bayesian approach to model calibration of low‐fidelity simulation models (2023)A modular Bayesian approach t…Towards improving the predictive capability of computer simulations by integrating inverse Uncertainty Quantification and quantitative validation with Bayesian hypothesis testing (2021)Towards improving the predict…Strength uncertainty analysis of composite turbine blade with small sample size (2021)Strength uncertainty analysis…Data-driven and active learning of variance-based sensitivity indices with Bayesian probabilistic integration (2021)Data-driven and active learni…Bayesian calibration of computer models based on Takagi–Sugeno fuzzy models (2021)Bayesian calibration of compu…A comprehensive framework for model validation and reliability assessment of container crane structures (2020)A comprehensive framework for…A New Interval Area Metric for Model Validation With Limited Experimental Data (2018)A New Interval Area Metric fo…Why Do Verification and Validation? 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References

  • 2001Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates6,377 cited
  • 1988Empirical Model Building and Response Surfaces5,235 cited
  • 1999A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output2,274 cited
  • 2011A comprehensive framework for verification, validation, and uncertainty quantification in scientific computing810 cited
  • 2007A Framework for Validation of Computer Models656 cited
  • 2006Measures of agreement between computation and experiment: Validation metrics494 cited
  • 2009Guide for Verification and Validation in Computational Solid Mechanics390 cited
  • 2012Quantification of Model Uncertainty: Calibration, Model Discrepancy, and Identifiability332 cited
  • 2008A comparative study of uncertainty propagation methods for black-box-type problems331 cited
  • 2007Model validation and predictive capability for the thermal challenge problem322 cited
  • 2011Toward a Better Understanding of Model Validation Metrics175 cited
  • 2005Understanding the Effects of Model Uncertainty in Robust Design With Computer Experiments157 cited
  • 2012Improving Identifiability in Model Calibration Using Multiple Responses136 cited
  • 2007A Design-Driven Validation Approach Using Bayesian Prediction Models109 cited

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  • 2013Reliability-Based Design Optimization with Model Bias and Data Uncertainty75 cited
  • 2014New validation metrics for models with multiple correlated responses62 cited
  • Cited by

    • 2021Data-driven and active learning of variance-based sensitivity indices with Bayesian probabilistic integration38 cited
    • 2021Towards improving the predictive capability of computer simulations by integrating inverse Uncertainty Quantification and quantitative validation with Bayesian hypothesis testing15 cited
    • 2021Bayesian calibration of computer models based on Takagi–Sugeno fuzzy models12 cited
    • 2018A New Interval Area Metric for Model Validation With Limited Experimental Data10 cited
    • 2016Why Do Verification and Validation?9 cited
    • 2021Strength uncertainty analysis of composite turbine blade with small sample size8 cited
    • 2020A comprehensive framework for model validation and reliability assessment of container crane structures8 cited
    • 2023Probabilistic Validation: Theoretical Foundation and Methodological Platform7 cited
    • 2023A modular Bayesian approach to model calibration of low‐fidelity simulation models7 cited