
Structure exploiting methods for fast uncertainty quantification in multiphase flow through heterogeneous media
We present a computational framework for dimension reduction and surroga...
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Optimal design of largescale Bayesian linear inverse problems under reducible model uncertainty: good to know what you don't know
We consider optimal design of infinitedimensional Bayesian linear inver...
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Global sensitivity analysis informed model reduction and selection applied to a Valsalva maneuver model
In this study, we develop a methodology for model reduction and selectio...
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Monte Carlo Estimators for the Schatten pnorm of Symmetric Positive Semidefinite Matrices
We present numerical methods for computing the Schatten pnorm of positi...
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Multiscale global sensitivity analysis for stochastic chemical systems
Sensitivity analysis is routinely performed on simplified surrogate mode...
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Optimal experimental design under irreducible uncertainty for inverse problems governed by PDEs
We present a method for computing Aoptimal sensor placements for infini...
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Randomization and reweighted ℓ_1minimization for Aoptimal design of linear inverse problems
We consider optimal design of PDEbased Bayesian linear inverse problems...
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Derivativebased global sensitivity analysis for models with highdimensional inputs and functional outputs
We present a framework for derivativebased global sensitivity analysis ...
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Efficient Marginalizationbased MCMC Methods for Hierarchical Bayesian Inverse Problems
Hierarchical models in Bayesian inverse problems are characterized by an...
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Sensitivitydriven adaptive construction of reducedspace surrogates
We develop a systematic approach for surrogate model construction in red...
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GoalOriented Optimal Design of Experiments for LargeScale Bayesian Linear Inverse Problems
We develop a framework for goal oriented optimal design of experiments (...
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Variancebased sensitivity analysis for timedependent processes
The global sensitivity analysis of timedependent processes requires his...
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Alen Alexanderian
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