32 citations · 47 across the 9 of their papers we have counts for
10 papers
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…
Optimization-Based MCMC Methods for Nonlinear Hierarchical Statistical Inverse Problems
Johnathan Bardsley, Tiangang Cui
In many hierarchical inverse problems, not only do we want to estimate high- or infinite-dimensional model parameters in the parameter-to-observable maps, but we also have to estim…
Scalable optimization-based sampling on function space
Johnathan Bardsley, Tiangang Cui, Youssef Marzouk +1
Optimization-based samplers such as randomize-then-optimize (RTO) [2] provide an efficient and parallellizable approach to solving large-scale Bayesian inverse problems. These meth…
Semivariogram methods for modeling Whittle-Matérn priors in Bayesian inverse problems
Richard D. Brown, Johnathan M. Bardsley, Tiangang Cui
We present a new technique, based on semivariogram methodology, for obtaining point estimates for use in prior modeling for solving Bayesian inverse problems. This method requires…
Efficient Marginalization-based MCMC Methods for Hierarchical Bayesian Inverse Problems
Arvind K. Saibaba, Johnathan Bardsley, D. Andrew Brown +1
Hierarchical models in Bayesian inverse problems are characterized by an assumed prior probability distribution for the unknown state and measurement error precision, and hyper-pri…
Parameter and Uncertainty Estimation for Dynamical Systems Using Surrogate Stochastic Processes
M. Chung, M. Binois, R. B. Gramacy +3
Inference on unknown quantities in dynamical systems via observational data is essential for providing meaningful insight, furnishing accurate predictions, enabling robust control,…
Point Spread Function Estimation in X-ray Imaging with Partially Collapsed Gibbs Sampling
Kevin T. Joyce, Johnathan M. Bardsley, Aaron Luttman
The point spread function (PSF) of a translation invariant imaging system is its impulse response, which cannot always be measured directly. This is the case in high energy X-ray r…
Bayesian inverse problems with priors: a Randomize-then-Optimize approach
Zheng Wang, Johnathan M. Bardsley, Antti Solonen +2
Prior distributions for Bayesian inference that rely on the -norm of the parameters are of considerable interest, in part because they promote parameter fields with less regul…
Analysis of the Gibbs sampler for hierarchical inverse problems
Sergios Agapiou, Johnathan M. Bardsley, Omiros Papaspiliopoulos +1
Many inverse problems arising in applications come from continuum models where the unknown parameter is a field. In practice the unknown field is discretized resulting in a problem…
Least-squares methods with Poissonian noise: an analysis and a comparison with the Richardson-Lucy algorithm
R. Vio, J. Bardsley, W. Wamsteker
It is well-known that the noise associated with the collection of an astronomical image by a CCD camera is, in large part, Poissonian. One would expect, therefore, that computation…