This paper aims to examine the characteristics of the posterior distribu...
A recent article on generalised linear mixed model asymptotics, Jiang et...
We extend a recently established asymptotic normality theorem for genera...
We use Bayesian model selection paradigms, such as group least absolute
...
Linear mixed models are a versatile statistical tool to study data by
ac...
We present a framework for fitting inverse problem models via variationa...
We derive streamlined mean field variational Bayes algorithms for fittin...
We derive and present explicit algorithms to facilitate streamlined comp...
We define and solve classes of sparse matrix problems that arise in
mult...
Expectation propagation is a general approach to fast approximate infere...