78 citations · 290 across the 25 of their papers we have counts for
5 papers · 1 filter
Sparse Bayesian mass-mapping with uncertainties: peak statistics and feature locations
Matthew A. Price, Xiaohao Cai, Jason D. McEwen +1
Weak lensing convergence maps - upon which higher order statistics can be calculated - can be recovered from observations of the shear field by solving the lensing inverse problem.…
Sparse Bayesian mass-mapping with uncertainties: local credible intervals
Matthew A. Price, Xiaohao Cai, Jason D. McEwen +2
Until recently mass-mapping techniques for weak gravitational lensing convergence reconstruction have lacked a principled statistical framework upon which to quantify reconstructio…
Sparse Bayesian mass-mapping with uncertainties: hypothesis testing of structure
Matthew A. Price, Jason D. McEwen, Xiaohao Cai +2
A crucial aspect of mass-mapping, via weak lensing, is quantification of the uncertainty introduced during the reconstruction process. Properly accounting for these errors has been…
Quantifying Uncertainty in High Dimensional Inverse Problems by Convex Optimisation
Xiaohao Cai, Marcelo Pereyra, Jason D. McEwen
Inverse problems play a key role in modern image/signal processing methods. However, since they are generally ill-conditioned or ill-posed due to lack of observations, their soluti…
Linkage between piecewise constant Mumford-Shah model and ROF model and its virtue in image segmentation
Xiaohao Cai, Raymond Chan, Carola-Bibiane Schonlieb +2
The piecewise constant Mumford-Shah (PCMS) model and the Rudin-Osher-Fatemi (ROF) model are two important variational models in image segmentation and image restoration, respective…