13 citations · 25 across the 9 of their papers we have counts for
5 papers · 1 filter
CUQIpy: II. Computational uncertainty quantification for PDE-based inverse problems in Python
Amal M A Alghamdi, Nicolai A B Riis, Babak M Afkham +4
Inverse problems, particularly those governed by Partial Differential Equations (PDEs), are prevalent in various scientific and engineering applications, and uncertainty quantifica…
CUQIpy: I. Computational uncertainty quantification for inverse problems in Python
Nicolai A B Riis, Amal M A Alghamdi, Felipe Uribe +4
This paper introduces CUQIpy, a versatile open-source Python package for computational uncertainty quantification (UQ) in inverse problems, presented as Part I of a two-part series…
Inferring Object Boundaries and their Roughness with Uncertainty Quantification
Babak Maboudi Afkham, Nicolai André Brogaard Riis, Yiqiu Dong +1
This work describes a Bayesian framework for reconstructing the boundaries that represent targeted features in an image, as well as the regularity (i.e., roughness vs. smoothness)…
Structural Gaussian Priors for Bayesian CT reconstruction of Subsea Pipes
Silja L. Christensen, Nicolai A. B. Riis, Felipe Uribe +1
A non-destructive testing (NDT) application of X-ray computed tomography (CT) is inspection of subsea pipes in operation via 2D cross-sectional scans. Data acquisition is time-cons…
Fixing Nonconvergence of Algebraic Iterative Reconstruction with an Unmatched Backprojector
Yiqiu Dong, Per Christian Hansen, Michiel E. Hochstenbach +1
We consider algebraic iterative reconstruction methods with applications in image reconstruction. In particular, we are concerned with methods based on an unmatched projector/backp…