Richard G. Everitt | DeepAI

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Featured Co-authors

Christopher Drovandi
43 publications
Adam M. Johansen
18 publications
Andrew Golightly
15 publications
Dennis Prangle
13 publications
Umberto Picchini
9 publications
Mark Bell
7 publications
Philip Maybank
2 publications
Thomas Thorne
2 publications
Felipe J Medina-Aguayo
2 publications
Paulina A. Rowińska
1 publication
Melina Evdemon-Hogan
1 publication

∙ 11/03/2022

Rare event ABC-SMC^2

Approximate Bayesian computation (ABC) is a well-established family of M...

0 Ivis Kerama, et al. ∙

∙ 08/18/2019

Revisiting the balance heuristic for estimating normalising constants

Multiple importance sampling estimators are widely used for computing in...

0 Felipe J Medina-Aguayo, et al. ∙

∙ 06/05/2019

Ensemble MCMC: Accelerating Pseudo-Marginal MCMC for State Space Models using the Ensemble Kalman Filter

Particle Markov chain Monte Carlo (pMCMC) is now a popular method for pe...

0 Christopher Drovandi, et al. ∙

∙ 05/20/2019

Stratified sampling and resampling for approximate Bayesian computation

Approximate Bayesian computation (ABC) is computationally intensive for ...

0 Umberto Picchini, et al. ∙

∙ 11/15/2017

Bootstrapped synthetic likelihood

The development of approximate Bayesian computation (ABC) and synthetic ...

0 Richard G. Everitt, et al. ∙

∙ 10/12/2017

Marginal sequential Monte Carlo for doubly intractable models

Bayesian inference for models that have an intractable partition functio...

0 Richard G. Everitt, et al. ∙

∙ 08/07/2017

Delayed acceptance ABC-SMC

Approximate Bayesian computation (ABC) is now an established technique f...

0 Richard G. Everitt, et al. ∙

∙ 04/27/2016

An ABC interpretation of the multiple auxiliary variable method

We show that the auxiliary variable method (Møller et al., 2006; Murray ...

0 Dennis Prangle, et al. ∙

∙ 04/01/2015

Bayesian model comparison with un-normalised likelihoods

Models for which the likelihood function can be evaluated only up to a p...

0 Richard G. Everitt, et al. ∙

∙ 03/14/2012

Bayesian Parameter Estimation for Latent Markov Random Fields and Social Networks

Undirected graphical models are widely used in statistics, physics and m...

0 Richard G. Everitt, et al. ∙

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