13 citations · 24 across the 6 of their papers we have counts for
6 papers
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…
Horseshoe priors for edge-preserving linear Bayesian inversion
Felipe Uribe, Yiqiu Dong, Per Christian Hansen
In many large-scale inverse problems, such as computed tomography and image deblurring, characterization of sharp edges in the solution is desired. Within the Bayesian approach to…
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…
A hybrid Gibbs sampler for edge-preserving tomographic reconstruction with uncertain view angles
Felipe Uribe, Johnathan M. Bardsley, Yiqiu Dong +2
In computed tomography, data consist of measurements of the attenuation of X-rays passing through an object. The goal is to reconstruct the linear attenuation coefficient of the ob…
Cross-entropy-based importance sampling with failure-informed dimension reduction for rare event simulation
Felipe Uribe, Iason Papaioannou, Youssef M. Marzouk +1
The estimation of rare event or failure probabilities in high dimensions is of interest in many areas of science and technology. We consider problems where the rare event is expres…