5 citations · 5 across the 6 of their papers we have counts for
16 papers
A new perspective on parameter study of optimization problems
Alen Alexanderian, Joseph Hart, Mason Stevens
We provide a new perspective on the study of parameterized optimization problems. Our approach combines methods for post-optimal sensitivity analysis and ordinary differential equa…
Hyper-differential sensitivity analysis for nonlinear Bayesian inverse problems
Isaac Sunseri, Alen Alexanderian, Joseph Hart +1
We consider hyper-differential sensitivity analysis (HDSA) of nonlinear Bayesian inverse problems governed by PDEs with infinite-dimensional parameters. In previous works, HDSA has…
Global sensitivity analysis of rare event probabilities
Michael Merritt, Alen Alexanderian, Pierre Gremaud
By their very nature, rare event probabilities are expensive to compute; they are also delicate to estimate as their value strongly depends on distributional assumptions on the mod…
Optimal design of large-scale Bayesian linear inverse problems under reducible model uncertainty: good to know what you don't know
Alen Alexanderian, Noemi Petra, Georg Stadler +1
We consider optimal design of infinite-dimensional Bayesian linear inverse problems governed by partial differential equations that contain secondary reducible model uncertainties,…
Monte Carlo Estimators for the Schatten p-norm of Symmetric Positive Semidefinite Matrices
Ethan Dudley, Arvind K. Saibaba, Alen Alexanderian
We present numerical methods for computing the Schatten -norm of positive semi-definite matrices. Our motivation stems from uncertainty quantification and optimal experimental d…
Optimal Experimental Design for Infinite-dimensional Bayesian Inverse Problems Governed by PDEs: A Review
Alen Alexanderian
We present a review of methods for optimal experimental design (OED) for Bayesian inverse problems governed by partial differential equations with infinite-dimensional parameters.…