A Nonnegatively Constrained Convex Programming Method for Image Reconstruction. - Johnathan M. Bardsley; Curtis R. Vogel (SIAM J. Sci. Comput., 2004)

Covariance-Preconditioned Iterative Methods for Nonnegatively Constrained Astronomical Imaging. - Johnathan M. Bardsley; James G. Nagy (SIAM J. Matrix Anal. Appl., 2006)

A Variational Approach to Video Segmentation for Botanical Data. - Aaron Luttman; John Bardsley (SIAM J. Sci. Comput., 2007)

Wavefront Reconstruction Methods for Adaptive Optics Systems on Ground-Based Telescopes. - Johnathan M. Bardsley (SIAM J. Matrix Anal. Appl., 2008)

Erratum: A Variational Approach to Video Segmentation for Botanical Data. - Aaron Luttman; John Bardsley (SIAM J. Sci. Comput., 2008)

An Efficient Phase and Object Estimation Scheme for Phase-Diversity Time Series Data. - Johnathan M. Bardsley (IEEE Trans. Image Process., 2008)

Total variation-penalized Poisson likelihood estimation for ill-posed problems. - Johnathan M. Bardsley; Aaron Luttman (Adv. Comput. Math., 2009)

An Iterative Method for Edge-Preserving MAP Estimation When Data-Noise Is Poisson. - Johnathan M. Bardsley; John Goldes (SIAM J. Sci. Comput., 2010)

Structured linear algebra problems in adaptive optics imaging. - Johnathan M. Bardsley; Sarah Knepper; James G. Nagy (Adv. Comput. Math., 2011)

Regularization parameter selection and an efficient algorithm for total variation-regularized positron emission tomography. - Johnathan M. Bardsley; John Goldes (Numer. Algorithms, 2011)

MCMC-Based Image Reconstruction with Uncertainty Quantification. - Johnathan M. Bardsley (SIAM J. Sci. Comput., 2012)

Krylov space approximate Kalman filtering. - Johnathan M. Bardsley; Albert Parker; Antti Solonen; Marylesa Howard (Numer. Linear Algebra Appl., 2013)

Analysis of the Gibbs Sampler for Hierarchical Inverse Problems. - Sergios Agapiou; Johnathan M. Bardsley; Omiros Papaspiliopoulos; Andrew M. Stuart (SIAM/ASA J. Uncertain. Quantification, 2014)

Randomize-Then-Optimize: A Method for Sampling from Posterior Distributions in Nonlinear Inverse Problems. - Johnathan M. Bardsley; Antti Solonen; Heikki Haario; Marko Laine (SIAM J. Sci. Comput., 2014)

Randomize-Then-Optimize for Sampling and Uncertainty Quantification in Electrical Impedance Tomography. - Johnathan M. Bardsley; Aku Seppänen; Antti Solonen; Heikki Haario; Jari P. Kaipio (SIAM/ASA J. Uncertain. Quantification, 2015)

Bayesian Inverse Problems with l1 Priors: A Randomize-Then-Optimize Approach. - Zheng Wang; Johnathan M. Bardsley; Antti Solonen; Tiangang Cui; Youssef M. Marzouk (SIAM J. Sci. Comput., 2017)

Point Spread Function Estimation in X-Ray Imaging with Partially Collapsed Gibbs Sampling. - Kevin T. Joyce; Johnathan M. Bardsley; Aaron Luttman (SIAM J. Sci. Comput., 2018)

Efficient Marginalization-Based MCMC Methods for Hierarchical Bayesian Inverse Problems. - Arvind K. Saibaba; Johnathan M. Bardsley; D. Andrew Brown; Alen Alexanderian (SIAM/ASA J. Uncertain. Quantification, 2019)

Parameter and Uncertainty Estimation for Dynamical Systems Using Surrogate Stochastic Processes. - Matthias Chung; Mickaël Binois; Robert B. Gramacy; Johnathan M. Bardsley; David J. Moquin; Amanda P. Smith; Amber M. Smith (SIAM J. Sci. Comput., 2019)

Optimization-Based MCMC Methods for Nonlinear Hierarchical Statistical Inverse Problems. - Johnathan M. Bardsley; Tiangang Cui (CoRR, 2020)

Scalable Optimization-Based Sampling on Function Space. - Johnathan M. Bardsley; Tiangang Cui; Youssef M. Marzouk; Zheng Wang (SIAM J. Sci. Comput., 2020)

MCMC Algorithms for Computational UQ of Nonnegativity Constrained Linear Inverse Problems. - Johnathan M. Bardsley; Per Christian Hansen (SIAM J. Sci. Comput., 2020)

Optimization-Based Markov Chain Monte Carlo Methods for Nonlinear Hierarchical Statistical Inverse Problems. - Johnathan M. Bardsley; Tiangang Cui (SIAM/ASA J. Uncertain. Quantification, 2021)

Matlab Software for Supervised Habitat Mapping of Freshwater Systems Using Image Processing. - Johnathan M. Bardsley; Marylesa Howard; Mark Lorang (Remote. Sens., 2021)

A Hybrid Gibbs Sampler for Edge-Preserving Tomographic Reconstruction with Uncertain View Angles. - Felipe Uribe; Johnathan M. Bardsley; Yiqiu Dong; Per Christian Hansen; Nicolai André Brogaard Riis (SIAM/ASA J. Uncertain. Quantification, 2022)