Multilevel Monte Carlo Analysis for Optimal Control of Elliptic PDEs with Random Coefficients-Reference-Cited by-同舟云学术

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Multilevel Monte Carlo Analysis for Optimal Control of Elliptic PDEs with Random Coefficients

Published:2017-01 Issue:1 Volume:5 Page:466-492
ISSN:2166-2525
Container-title:SIAM/ASA Journal on Uncertainty Quantification
language:en
Short-container-title:SIAM/ASA J. Uncertainty Quantification

Author:

Ali Ahmad Ahmad,Ullmann Elisabeth,Hinze Michael

Publisher

Society for Industrial & Applied Mathematics (SIAM)

Subject

Applied Mathematics,Discrete Mathematics and Combinatorics,Statistics, Probability and Uncertainty,Modeling and Simulation,Statistics and Probability

Link

https://epubs.siam.org/doi/pdf/10.1137/16M109870X

Reference42 articles.

1. A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data

2. Multi-level Monte Carlo Finite Element method for elliptic PDEs with stochastic coefficients

3. Low-rank solvers for unsteady Stokes–Brinkman optimal control problem with random data

4. Block-Diagonal Preconditioning for Optimal Control Problems Constrained by PDEs with Uncertain Inputs

5. Convergence analysis of multilevel Monte Carlo variance estimators and application for random obstacle problems

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3. Robustness of reaction–diffusion PDEs predictor-feedback to stochastic delay perturbations;Automatica;2024-09

4. One-Shot Learning of Surrogates in PDE-Constrained Optimization under Uncertainty;SIAM/ASA Journal on Uncertainty Quantification;2024-06-12

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