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A generalized approximate control variate framework for multifidelity uncertainty quantification
5 references·16 citing·37 second hop
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this work references cited by second hop

References

  • 2008Multilevel Monte Carlo Path Simulation1,436 cited
  • 2018Survey of Multifidelity Methods in Uncertainty Propagation, Inference, and Optimization1,072 cited
  • 2011Multilevel Monte Carlo methods and applications to elliptic PDEs with random coefficients490 cited
  • 2016Optimal Model Management for Multifidelity Monte Carlo Estimation243 cited
  • 2014Multifidelity approaches for optimization under uncertainty198 cited

Cited by

  • 2020Multilevel and multifidelity uncertainty quantification for cardiovascular hemodynamics99 cited
  • 2021Multifidelity prediction in wildfire spread simulation: Modeling, uncertainty quantification and sensitivity analysis55 cited
  • 2020A MULTI-FIDELITY NEURAL NETWORK SURROGATE SAMPLING METHOD FOR UNCERTAINTY QUANTIFICATION54 cited
  • 2022Active learning with multifidelity modeling for efficient rare event simulation39 cited
  • 2022Reliability estimation of an advanced nuclear fuel using coupled active learning, multifidelity modeling, and subset simulation33 cited
  • 2021Accelerated basis adaptation in homogeneous chaos spaces26 cited
  • 2020Bi-fidelity stochastic gradient descent for structural optimization under uncertainty25 cited
  • 2023Multifidelity uncertainty quantification with models based on dissimilar parameters24 cited
  • 2022A generalized probabilistic learning approach for multi-fidelity uncertainty quantification in complex physical simulations

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22 cited
  • 2021On the optimization of approximate control variates with parametrically defined estimators21 cited
  • 2022Comparing multi-index stochastic collocation and multi-fidelity stochastic radial basis functions for forward uncertainty quantification of ship resistance19 cited
  • 2023PyApprox: A software package for sensitivity analysis, Bayesian inference, optimal experimental design, and multi-fidelity uncertainty quantification and surrogate modeling19 cited
  • 2021Uncertainty Quantification for the BGK Model of the Boltzmann Equation Using Multilevel Variance Reduced Monte Carlo Methods19 cited
  • 2023UQpy v4.1: Uncertainty quantification with Python19 cited
  • 2023Context-aware learning of hierarchies of low-fidelity models for multi-fidelity uncertainty quantification17 cited
  • 2021Asymptotic Analysis of Multilevel Best Linear Unbiased Estimators17 cited