Asynchronous Anytime Sequential Monte Carlo
Paige, B
Wood, F
Doucet, A
Teh, Y
(10 Jul 2014)
doi:10.48550/arxiv.1407.2864
Particle Gibbs Split-Merge Sampling for Bayesian Inference in Mixture Models
Bouchard-Côté, A
Doucet, A
Roth, A
(11 Aug 2015)
doi:10.48550/arxiv.1508.02663
On embedded hidden Markov models and particle Markov chain Monte Carlo methods
Finke, A
Doucet, A
Johansen, A
(27 Oct 2016)
doi:10.48550/arxiv.1610.08962
A Backward Particle Interpretation of Feynman-Kac Formulae
Del Moral, P
Doucet, A
Singh, S
(18 Aug 2009)
doi:10.48550/arxiv.0908.2556
Sequentially interacting Markov chain Monte Carlo methods
Brockwell, A
Del Moral, P
Doucet, A
(12 Nov 2012)
doi:10.48550/arxiv.1211.2582
Reversible Jump MCMC Simulated Annealing for Neural Networks
Andrieu, C
de Freitas, N
Doucet, A
(16 Jan 2013)
doi:10.48550/arxiv.1301.3833
Perfect simulation using atomic regeneration with application to Sequential Monte Carlo
Lee, A
Doucet, A
Łatuszyński, K
(22 Jul 2014)
doi:10.48550/arxiv.1407.5770
Gibbs flow for approximate transport with applications to Bayesian computation
Heng, J
Doucet, A
Pokern, Y
(29 Sep 2015)
doi:10.48550/arxiv.1509.08787
Grouping Priors and the Bayesian Elastic Net
Bornn, L
Gottardo, R
Doucet, A
(22 Jan 2010)
doi:10.48550/arxiv.1001.4083
Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks
Doucet, A
de Freitas, N
Murphy, K
Russell, S
(16 Jan 2013)
doi:10.48550/arxiv.1301.3853