180 citations · 1.1k across the 26 of their papers we have counts for
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A Generalized Approximate Control Variate Framework for Multifidelity Uncertainty Quantification
Alex A. Gorodetsky, Gianluca Geraci, Mike Eldred +1
We describe and analyze a variance reduction approach for Monte Carlo (MC) sampling that accelerates the estimation of statistics of computationally expensive simulation models usi…
Time and Frequency Domain Methods for Basis Selection in Random Linear Dynamical Systems
John D. Jakeman, Roland Pulch
Polynomial chaos methods have been extensively used to analyze systems in uncertainty quantification. Furthermore, several approaches exist to determine a low-dimensional approxima…
Convergence of Probability Densities using Approximate Models for Forward and Inverse Problems in Uncertainty Quantification
T. Butler, J. D. Jakeman, T. Wildey
We analyze the convergence of probability density functions utilizing approximate models for both forward and inverse problems. We consider the standard forward uncertainty quantif…
Gradient-based Optimization for Regression in the Functional Tensor-Train Format
Alex A. Gorodetsky, John D. Jakeman
We consider the task of low-multilinear-rank functional regression, i.e., learning a low-rank parametric representation of functions from scattered real-valued data. Our first cont…