38 citations · 86 across the 15 of their papers we have counts for
4 papers · 1 filter
Warped Gradient-Enhanced Gaussian Process Surrogate Models for Exponential Family Likelihoods with Intractable Normalizing Constants
Quan Vu, Matthew T. Moores, Andrew Zammit-Mangion
Markov chain Monte Carlo methods for exponential family models with intractable normalizing constant, such as the exchange algorithm, require simulations of the sufficient statisti…
Bayesian Computation with Intractable Likelihoods
Matthew T. Moores, Anthony N. Pettitt, Kerrie Mengersen
This article surveys computational methods for posterior inference with intractable likelihoods, that is where the likelihood function is unavailable in closed form, or where evalu…
Scalable Bayesian Inference for the Inverse Temperature of a Hidden Potts Model
Matthew T. Moores, Geoff K. Nicholls, Anthony N. Pettitt +1
The inverse temperature parameter of the Potts model governs the strength of spatial cohesion and therefore has a major influence over the resulting model fit. A difficulty arises…
Pre-processing for approximate Bayesian computation in image analysis
Matthew T. Moores, Christopher C. Drovandi, Kerrie Mengersen +1
Most of the existing algorithms for approximate Bayesian computation (ABC) assume that it is feasible to simulate pseudo-data from the model at each iteration. However, the computa…