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20122026
most citedGoal-Oriented Optimal Design of Experiments for Large-Scale Bayesian Linear Inverse Problems

59 citations · 220 across the 52 of their papers we have counts for

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Showing 2019Show all

3 papers · 1 filter

math.NA2019

Randomization and reweighted -minimization for A-optimal design of linear inverse problems

Elizabeth Herman, Alen Alexanderian, Arvind K. Saibaba

We consider optimal design of PDE-based Bayesian linear inverse problems with infinite-dimensional parameters. We focus on the A-optimal design criterion, defined as the average po…

math.NA2019

Randomized algorithms for low-rank tensor decompositions in the Tucker format

Rachel Minster, Arvind K. Saibaba, Misha E. Kilmer

Many applications in data science and scientific computing involve large-scale datasets that are expensive to store and compute with, but can be efficiently compressed and stored i…

math.NA2019

Randomized Discrete Empirical Interpolation Method for Nonlinear Model Reduction

Arvind K. Saibaba

Discrete empirical interpolation method (DEIM) is a popular technique for nonlinear model reduction and it has two main ingredients: an interpolating basis that is computed from a…