3 papers
stat.CO2024
Grouped approximate control variate estimators
Alex A. Gorodetsky, John D. Jakeman, Michael S. Eldred
This paper analyzes the approximate control variate (ACV) approach to multifidelity uncertainty quantification in the case where weighted estimators are combined to form the compon…
stat.CO2023
Multilevel Monte Carlo estimators for derivative-free optimization under uncertainty
Friedrich Menhorn, Gianluca Geraci, D. Thomas Seidl +3
Optimization is a key tool for scientific and engineering applications, however, in the presence of models affected by uncertainty, the optimization formulation needs to be extende…
physics.data-an2023
Multifidelity uncertainty quantification with models based on dissimilar parameters
Xiaoshu Zeng, Gianluca Geraci, Michael S. Eldred +3
Multifidelity uncertainty quantification (MF UQ) sampling approaches have been shown to significantly reduce the variance of statistical estimators while preserving the bias of the…