720 citations · 1.4k across the 27 of their papers we have counts for
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Uniform Ergodicity of the Iterated Conditional SMC and Geometric Ergodicity of Particle Gibbs samplers
Christophe Andrieu, Anthony Lee, Matti Vihola
We establish quantitative bounds for rates of convergence and asymptotic variances for iterated conditional sequential Monte Carlo (i-cSMC) Markov chains and associated particle Gi…
Quantitative convergence rates for sub-geometric Markov chains
Christophe Andrieu, Gersende Fort, Matti Vihola
We provide explicit expressions for the constants involved in the characterisation of ergodicity of sub-geometric Markov chains. The constants are determined in terms of those appe…
Kernel Adaptive Metropolis-Hastings
Dino Sejdinovic, Heiko Strathmann, Maria Lomeli Garcia +2
A Kernel Adaptive Metropolis-Hastings algorithm is introduced, for the purpose of sampling from a target distribution with strongly nonlinear support. The algorithm embeds the traj…
Reversible Jump MCMC Simulated Annealing for Neural Networks
Christophe Andrieu, Nando de Freitas, Arnaud Doucet
We propose a novel reversible jump Markov chain Monte Carlo (MCMC) simulated annealing algorithm to optimize radial basis function (RBF) networks. This algorithm enables us to maxi…