Multifidelity importance sampling
type: Item
instance of: scholarly article
title: Multifidelity importance sampling
zbMATH Open document ID: 1426.62087
author: Benjamin Peherstorfer
author: Tiangang Cui
author: Karen Willcox
author: Youssef M. Marzouk
published in: Computer Methods in Applied Mechanics and Engineering
publication date: 2019-05-17T00:00:00Z
Mathematics Subject Classification ID: 62F10
Mathematics Subject Classification ID: 65C05
zbMATH DE Number: 7056327
zbMATH Keywords: Monte Carlo method
zbMATH Keywords: importance sampling
zbMATH Keywords: surrogate modeling
zbMATH Keywords: multifidelity methods
describes a project that uses: libagf
describes a project that uses: PRMLT
describes a project that uses: Loewner
describes a project that uses: Matlab
MaRDI profile type: Publication
full work available at URL: j.cma.2015.12.002
OpenAlex ID: W2193006036
cites work: Evaluation of failure probability via surrogate models
cites work: Q4828566
cites work: Q4869639
cites work: Q4778523
cites work: Optimization of computer simulation models with rare events
cites work: A tutorial on the cross-entropy method
cites work: Convergence of adaptive mixtures of importance sampling schemes
cites work: Minimum variance importance samplingviaPopulation Monte Carlo
cites work: Adaptive Multiple Importance Sampling
cites work: On control variate estimators
cites work: Multilevel Monte Carlo Path Simulation
cites work: Multilevel Monte Carlo methods and applications to elliptic PDEs with random coefficients
cites work: Multifidelity approaches for optimization under uncertainty
cites work: Sampling and Low-Rank Tensor Approximation of the Response Surface
cites work: An efficient surrogate-based method for computing rare failure probability
cites work: Accurate and efficient evaluation of failure probability for partial different equations with random input data
cites work: Reduced basis approximation and a posteriori error estimation for affinely parametrized elliptic coercive partial differential equations. Application to transport and continuum mechanics.
cites work: Efficient reduced-basis treatment of nonaffine and nonlinear partial differential equations
cites work: Q3394879
cites work: Data-driven parametrized model reduction in the Loewner framework
cites work: A Survey of Model Reduction by Balanced Truncation and Some New Results
cites work: Q4727203
cites work: Q5483032
cites work: Machine learning. A probabilistic perspective
cites work: Dynamic data-driven reduced-order models
cites work: Model Reduction for Large-Scale Systems with High-Dimensional Parametric Input Space
cites work: Convergence Rates of the POD–Greedy Method
cites work: A two-step certified reduced basis method
cites work: Supersensitivity due to uncertain boundary conditions
cites work: Nonlinear Model Reduction via Discrete Empirical Interpolation
cites work: Localized Discrete Empirical Interpolation Method
DOI: 10.1016/J.CMA.2015.12.002
description: scientific article