On Particle Methods for Parameter Estimation in State-Space Models
Kantas, N
Doucet, A
Singh, S
Maciejowski, J
Chopin, N
(30 Dec 2014)
doi:10.48550/arxiv.1412.8695
Asymptotic Properties of Recursive Maximum Likelihood Estimation in Non-Linear State-Space Models
Tadic, V
Doucet, A
(25 Jun 2018)
doi:10.48550/arxiv.1806.09571
Limit theorems for sequential MCMC methods
Finke, A
Doucet, A
Johansen, A
(03 Jul 2018)
doi:10.48550/arxiv.1807.01057
Efficient Bayesian Inference for Switching State-Space Models using Discrete Particle Markov Chain Monte Carlo Methods
Whiteley, N
Andrieu, C
Doucet, A
(10 Nov 2010)
doi:10.48550/arxiv.1011.2437
Interacting Particle Markov Chain Monte Carlo
Rainforth, T
Naesseth, C
Lindsten, F
Paige, B
van de Meent, J
Doucet, A
Wood, F
(16 Feb 2016)
doi:10.48550/arxiv.1602.05128
Forward Smoothing using Sequential Monte Carlo
Del Moral, P
Doucet, A
Singh, S
(24 Dec 2010)
doi:10.48550/arxiv.1012.5390
Uniform Stability of a Particle Approximation of the Optimal Filter Derivative
Del Moral, P
Doucet, A
Singh, S
(13 Jun 2011)
doi:10.48550/arxiv.1106.2525
On nonlinear Markov chain Monte Carlo
Andrieu, C
Jasra, A
Doucet, A
Del Moral, P
(15 Jul 2011)
doi:10.48550/arxiv.1107.3046
Interacting Markov chain Monte Carlo methods for solving nonlinear measure-valued equations
Del Moral, P
Doucet, A
(28 Sep 2010)
doi:10.48550/arxiv.1009.5749
On the Impact of the Activation Function on Deep Neural Networks Training
Hayou, S
Doucet, A
Rousseau, J
(18 Feb 2019)
doi:10.48550/arxiv.1902.06853