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Accurate Uncertainty Quantification Using Inaccurate Computational Models
7 references·16 citing·35 second hop
Accurate Uncertainty Quantification Using Inaccurate Computational Models (2009)Accurate Uncertainty Quantification Using…Sparse grid collocation schemes for stochastic natural convection problems (2007)Sparse grid collocation schem…Stochastic Approaches to Uncertainty Quantification in CFD Simulations (2005)Stochastic Approaches to Unce…High-Order Collocation Methods for Differential Equations with Random Inputs (2005)High-Order Collocation Method…Design and Modeling for Computer Experiments (2005)Design and Modeling for Compu…Estimation of small failure probabilities in high dimensions by subset simulation (2001)Estimation of small failure p…Stochastic Finite Elements: A Spectral Approach (1991)Stochastic Finite Elements: A…Design and Analysis of Computer Experiments (1989)Design and Analysis of Comput…Uncertainty quantification with high-dimensional correlated process variations for an in-situ thermal expansion coefficient test structure (2024)Uncertainty quantification wi…A multi-fidelity stochastic simulation scheme for estimation of small failure probabilities (2023)A multi-fidelity stochastic s…A generalized probabilistic learning approach for multi-fidelity uncertainty quantification in complex physical simulations (2022)A generalized probabilistic l…On the optimization of approximate control variates with parametrically defined estimators (2021)On the optimization of approx…Turboelectric Uncertainty Quantification and Error Estimation in Numerical Modelling (2020)Turboelectric Uncertainty Qua…Bi-fidelity stochastic gradient descent for structural optimization under uncertainty (2020)Bi-fidelity stochastic gradie…A Generalized Probabilistic Learning Approach for Multi-Fidelity Uncertainty Propagation in Complex Physical Simulations (2020)A Generalized Probabilistic L…Towards efficient uncertainty quantification with high-resolution morphodynamic models: A multifidelity approach applied to channel sedimentation (2019)Towards efficient uncertainty…Multifidelity approaches for uncertainty quantification (2019)Multifidelity approaches for …High-dimensional and higher-order multifidelity Monte Carlo estimators (2019)High-dimensional and higher-o…Efficient Possibilistic Uncertainty Analysis of a Car Crash Scenario Using a Multifidelity Approach (2019)Efficient Possibilistic Uncer…A data-driven framework for sparsity-enhanced surrogates with arbitrary mutually dependent randomness (2019)A data-driven framework for s…Efficient uncertainty quantification for impact analysis of human interventions in rivers (2018)Efficient uncertainty quantif…Multilevel Estimation of Rare Events (2015)Multilevel Estimation of Rare…Multifidelity Uncertainty Propagation for Optimization Under Uncertainty (2012)Multifidelity Uncertainty Pro…Iterative improvement of Bayesian parameter estimates for an engine model by means of experimental design (2011)Iterative improvement of Baye…Multilevel Monte Carlo Path Simulation (2008)Combining multiple surrogate models to accelerate failure probability estimation with expensive high-fidelity models (2017)Multifidelity Preconditioning of the Cross-Entropy Method for Rare Event Simulation and Failure Probability Estimation (2018)A scenario optimization approach to reliability-based and risk-based design: Soft-constrained modulation of failure probability bounds (2021)Verification and Validation in Computational Science and Engineering (1998)The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations (2002)Probabilistic collocation method for flow in porous media: Comparisons with other stochastic methods (2007)Point-Collocation Nonintrusive Polynomial Chaos Method for Stochastic Computational Fluid Dynamics (2010)Stochastic finite element methods for partial differential equations with random input data (2014)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)Design of Experiments (1936)Response Surface Methodology: Process and Product Optimization Using Designed Experiments (1996)Bayesian estimation of parametric uncertainties, quantification and reduction using optimal design of experiments for CO2 adsorption on amine sorbents (2015)Surrogate modeling for probability distribution estimation: Uniform or adaptive design? 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this work references cited by second hop

References

  • 1989Design and Analysis of Computer Experiments6,958 cited
  • 1991Stochastic Finite Elements: A Spectral Approach5,753 cited
  • 2001Estimation of small failure probabilities in high dimensions by subset simulation2,419 cited
  • 2005High-Order Collocation Methods for Differential Equations with Random Inputs1,522 cited
  • 2005Design and Modeling for Computer Experiments1,135 cited
  • 2007Sparse grid collocation schemes for stochastic natural convection problems401 cited
  • 2005Stochastic Approaches to Uncertainty Quantification in CFD Simulations281 cited

Cited by

  • 2011Iterative improvement of Bayesian parameter estimates for an engine model by means of experimental design60 cited
  • 2015Multilevel Estimation of Rare Events47 cited
  • 2018Efficient uncertainty quantification for impact analysis of human interventions in rivers26 cited
  • 2020Bi-fidelity stochastic gradient descent for structural optimization under uncertainty25 cited
  • 2022A generalized probabilistic learning approach for multi-fidelity uncertainty quantification in complex physical simulations22 cited
  • 2021On the optimization of approximate control variates with parametrically defined estimators21 cited
  • 2019Multifidelity approaches for uncertainty quantification15 cited

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

  • 2012Multifidelity Uncertainty Propagation for Optimization Under Uncertainty14 cited
  • 2023A multi-fidelity stochastic simulation scheme for estimation of small failure probabilities13 cited
  • 2019High-dimensional and higher-order multifidelity Monte Carlo estimators13 cited
  • 2020A Generalized Probabilistic Learning Approach for Multi-Fidelity Uncertainty Propagation in Complex Physical Simulations12 cited
  • 2019Towards efficient uncertainty quantification with high-resolution morphodynamic models: A multifidelity approach applied to channel sedimentation11 cited
  • 2020Turboelectric Uncertainty Quantification and Error Estimation in Numerical Modelling9 cited
  • 2019A data-driven framework for sparsity-enhanced surrogates with arbitrary mutually dependent randomness8 cited
  • 2019Efficient Possibilistic Uncertainty Analysis of a Car Crash Scenario Using a Multifidelity Approach7 cited
  • 2024Uncertainty quantification with high-dimensional correlated process variations for an in-situ thermal expansion coefficient test structure5 cited