26 citations · 91 across the 16 of their papers we have counts for
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Sampled Tikhonov Regularization for Large Linear Inverse Problems
J. Tanner Slagel, Julianne Chung, Matthias Chung +2
In this paper, we investigate iterative methods that are based on sampling of the data for computing Tikhonov-regularized solutions. We focus on very large inverse problems where a…
Uncertainty quantification in large Bayesian linear inverse problems using Krylov subspace methods
Arvind K. Saibaba, Julianne Chung, Katrina Petroske
For linear inverse problems with a large number of unknown parameters, uncertainty quantification remains a challenging task. In this work, we use Krylov subspace methods to approx…
Flexible Krylov methods for regularization
Julianne Chung, Silvia Gazzola
In this paper we develop flexible Krylov methods for efficiently computing regularized solutions to large-scale linear inverse problems with an fit-to-data term and an $\e…