most citedNoisy Monte Carlo: Convergence of Markov chains with approximate transition kernels

4 citations · 4 across the 1 of their papers we have counts for

collaborators

2 papers

stat.CO2017

Efficient MCMC for Gibbs Random Fields using pre-computation

Aidan Boland, Nial Friel, Florian Maire

Bayesian inference of Gibbs random fields (GRFs) is often referred to as a doubly intractable problem, since the likelihood function is intractable. The exploration of the posterio…

stat.ME2014★ 4 cited

Noisy Monte Carlo: Convergence of Markov chains with approximate transition kernels

P. Alquier, N. Friel, R. Everitt +1

Monte Carlo algorithms often aim to draw from a distribution by simulating a Markov chain with transition kernel such that is invariant under . However, there are ma…