Optimal experimental design under irreducible uncertainty for linear inverse problems governed by PDEs

DOI10.1088/1361-6420/ab89c5zbMath1443.62213arXiv1912.08915OpenAlexW3102913725WikidataQ114096874 ScholiaQ114096874MaRDI QIDQ3298402

K. Koval, Alen Alexanderian, Georg Stadler

Publication date: 14 July 2020

Published in: Inverse Problems (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1912.08915

zbMATH Keywords

inverse problemsmodel reductionmodel uncertaintyoptimal designpartial differential equation (PDE)subsurface flowoptimization under uncertainty

Mathematics Subject Classification ID

Optimal statistical designs (62K05) Bayesian inference (62F15) Inverse problems for PDEs (35R30) Applications of statistics to physics (62P35)

Related Items (8)

Learning physics-based models from data: perspectives from inverse problems and model reduction ⋮ Identification of model uncertainty via optimal design of experiments applied to a mechanical press ⋮ Stochastic Learning Approach for Binary Optimization: Application to Bayesian Optimal Design of Experiments ⋮ Optimal Experimental Design for Inverse Problems in the Presence of Observation Correlations ⋮ A greedy sensor selection algorithm for hyperparameterized linear Bayesian inverse problems with correlated noise models ⋮ Optimal Design of Large-scale Bayesian Linear Inverse Problems Under Reducible Model Uncertainty: Good to Know What You Don't Know ⋮ Optimal experimental design for infinite-dimensional Bayesian inverse problems governed by PDEs: a review ⋮ Joint estimation of Robin coefficient and domain boundary for the Poisson problem

Uses Software

• hIPPYlib

Cites Work

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