Particle ancestor sampling for near-degenerate or intractable state
transition models

Particle ancestor sampling for near-degenerate or intractable state transition models

23 May 2015

Fredrik Lindsten

Sumeetpal S. Singh

Thomas B. Schon

ArXiv (abs)PDF HTML

Papers citing "Particle ancestor sampling for near-degenerate or intractable state transition models"

10 / 10 papers shown

Title
Auxiliary MCMC and particle Gibbs samplers for parallelisable inference in latent dynamical systems Adrien Corenflos Simo Särkkä 64 0 0 01 Mar 2023
Nested Sequential Monte Carlo Methods C. A. Naesseth Fredrik Lindsten Thomas B. Schon 433 84 0 09 Feb 2015
Uniform ergodicity of the Particle Gibbs sampler Fredrik Lindsten Randal Douc Eric Moulines 91 54 0 03 Jan 2014
Particle Gibbs with Ancestor Sampling Fredrik Lindsten Michael I. Jordan Thomas B. Schon 115 252 0 03 Jan 2014
On particle Gibbs sampling Nicolas Chopin Sumeetpal S. Singh 97 103 0 06 Apr 2013
Convergence properties of pseudo-marginal Markov chain Monte Carlo algorithms Christophe Andrieu M. Vihola 88 127 0 04 Oct 2012
On Disturbance State-Space Models and the Particle Marginal Metropolis-Hastings Sampler Lawrence M. Murray E. Jones J. Parslow 78 31 0 28 Feb 2012
Parameter Estimation for Hidden Markov Models with Intractable Likelihoods Elena Ehrlich Sumeetpal S. Singh Ajay Jasra N. Kantas TPM 92 92 0 28 Mar 2011
Efficient Bayesian Inference for Switching State-Space Models using Discrete Particle Markov Chain Monte Carlo Methods N. Whiteley Christophe Andrieu Arnaud Doucet 101 77 0 10 Nov 2010
Metropolising forward particle filtering backward sampling and Rao-Blackwellisation of Metropolised particle smoothers Jimmy Olsson Tobias Rydén 57 5 0 09 Nov 2010

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