59 citations · 220 across the 52 of their papers we have counts for
7 papers · 1 filter
Hyper-differential sensitivity analysis in the context of Bayesian inference applied to ice-sheet problems
William Reese, Joseph Hart, Bart van Bloemen Waanders +3
Inverse problems constrained by partial differential equations (PDEs) play a critical role in model development and calibration. In many applications, there are multiple uncertain…
Tensor-based flow reconstruction from optimally located sensor measurements
Mohammad Farazmand, Arvind K. Saibaba
Reconstructing high-resolution flow fields from sparse measurements is a major challenge in fluid dynamics. Existing methods often vectorize the flow by stacking different spatial…
Hybrid Projection Methods for Solution Decomposition in Large-scale Bayesian Inverse Problems
Julianne Chung, Jiahua Jiang, Scot M. Miller +1
We develop hybrid projection methods for computing solutions to large-scale inverse problems, where the solution represents a sum of different stochastic components. Such scenarios…
Efficient algorithms for Bayesian Inverse Problems with Whittle--Matérn Priors
Harbir Antil, Arvind K. Saibaba
This paper tackles efficient methods for Bayesian inverse problems with priors based on Whittle--Matérn Gaussian random fields. The Whittle--Matérn prior is characterized by a mean…
Robust Parameter Identifiability Analysis via Column Subset Selection
Katherine J. Pearce, Ilse C. F. Ipsen, Mansoor A. Haider +2
We advocate a numerically reliable and accurate approach for practical parameter identifiability analysis: Applying column subset selection (CSS) to the sensitivity matrix, instead…
Parametric Level-sets Enhanced To Improve Reconstruction (PaLEnTIR)
Ege Ozsar, Misha Kilmer, Eric Miller +2
We introduce PaLEnTIR, a significantly enhanced parametric level-set (PaLS) method addressing the restoration and reconstruction of piecewise constant objects. Our key contribution…