Arnaud Doucet

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Christophe AndrieuProfessor of Statistics, University of BristolVerified email at bristol.ac.uk
Nando de FreitasCIFAR & DeepMindVerified email at google.com
Sumeetpal Sidhu SinghProfessor of Engineering Statistics and Head of the Signal Processing and Communications GroupVerified email at cam.ac.uk
Pierre Del MoralResearch Director, INRIA Bordeaux - Sud OuestVerified email at inria.fr
Adam M. JohansenUniversity of WarwickVerified email at warwick.ac.uk
Simon GodsillUniversity of CambridgeVerified email at eng.cam.ac.uk
Ajay JasraProfessor of Applied Mathematics & Statistics, KAUSTVerified email at kaust.edu.sa
Neil GordonDefence Science and Technology GroupVerified email at uq.edu.au
George DeligiannidisAssociate Professor in Statistics, University of OxfordVerified email at stats.ox.ac.uk
Yee Whye TehProfessor of Statistical Machine Learning, Oxford, Research Scientist, DeepMindVerified email at stats.ox.ac.uk
Ba-Ngu VoCurtin UniversityVerified email at curtin.edu.au
François CaronUniversity of OxfordVerified email at stats.ox.ac.uk
Chris HolmesVerified email at stats.ox.ac.uk
Kevin MurphyResearch Scientist, GoogleVerified email at google.com
Mike WestDuke UniversityVerified email at nc.rr.com
Soufiane HayouDepartment of Statistics, University of OxfordVerified email at stats.ox.ac.uk
Vikram KrishnamurthyProfessor, Cornell UniversityVerified email at cornell.edu
Emilien DupontPhD student, University of OxfordVerified email at stats.ox.ac.uk
Anthony LeeSchool of Mathematics, University of BristolVerified email at bristol.ac.uk
Dan CrisanProfessor of Mathematics, Imperial College LondonVerified email at imperial.ac.uk

Arnaud Doucet

Professor of Statistics, University of Oxford & Senior Research Scientist, Google DeepMind

Verified email at stats.ox.ac.uk - Homepage

Bayesian Inference Computational Statistics Machine Learning Monte Carlo methods


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Sequential Monte Carlo Methods in Practice A Doucet, N De Freitas, N Gordon Sequential monte carlo methods in practice, 2001	9984	2001
On sequential Monte Carlo sampling methods for Bayesian filtering A Doucet, S Godsill, C Andrieu Statistics and computing 10, 197-208, 2000	6263	2000
An introduction to MCMC for machine learning C Andrieu, N De Freitas, A Doucet, MI Jordan Machine learning 50, 5-43, 2003	3229	2003
A tutorial on particle filtering and smoothing: Fifteen years later A Doucet, AM Johansen Oxford Handbook of Nonlinear Filtering 12 (656-704), 3, 2011	2475	2011
The unscented particle filter R Van Der Merwe, A Doucet, N De Freitas, EA Wan Advances in Neural Information Processing Systems, 2000	2442	2000
Particle Markov chain Monte Carlo methods C Andrieu, A Doucet, R Holenstein Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2010	2360	2010
Rao-Blackwellised particle filtering for dynamic Bayesian networks A Doucet, N De Freitas, K Murphy, S Russell UAI 2000, 2000	1958*	2000
Sequential Monte Carlo samplers P Del Moral, A Doucet, A Jasra Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2006	1875	2006
Sequential Monte Carlo methods for multitarget filtering with random finite sets BN Vo, S Singh, A Doucet IEEE Transactions on Aerospace and electronic systems 41 (4), 1224-1245, 2005	1561	2005
An introduction to sequential Monte Carlo methods A Doucet, N De Freitas, N Gordon Sequential Monte Carlo methods in practice, 3-14, 2001	1517	2001
A survey of convergence results on particle filtering methods for practitioners D Crisan, A Doucet IEEE Transactions on signal processing 50 (3), 736-746, 2002	1281	2002
Particle filters for state estimation of jump Markov linear systems A Doucet, NJ Gordon, V Krishnamurthy IEEE Transactions on signal processing 49 (3), 613-624, 2001	1087	2001
On sequential simulation-based methods for Bayesian filtering A Doucet Technical Report CUED/F-INFENG/TR.310 Cambridge University, 1998	1055	1998
Monte Carlo smoothing for nonlinear time series SJ Godsill, A Doucet, M West Journal of the american statistical association, 2004	667	2004
Fast computation of Wasserstein barycenters M Cuturi, A Doucet Proceedings of the 31st International Conference on Machine Learning, 685-693, 2014	653	2014
Maintaining multi-modality through mixture tracking J Vermaak, A Doucet, P Patrick International Conference on Computer Vision, 1110, 2003	559	2003
An adaptive sequential Monte Carlo method for approximate Bayesian computation P Del Moral, A Doucet, A Jasra Statistics and computing 22, 1009-1020, 2012	542	2012
On particle methods for parameter estimation in state-space models N Kantas, A Doucet, SS Singh, JM Maciejowski, N Chopin Statistical Science 30 (3), 328--351, 2015	463	2015
Sequential Monte Carlo implementation of the PHD filter for multi-target tracking BN Vo, S Singh, A Doucet Proc. Int’l Conf. on Information Fusion, 792-799, 2003	447	2003
Particle methods for change detection, system identification, and control C Andrieu, A Doucet, SS Singh, VB Tadic Proceedings of the IEEE 92 (3), 423-438, 2004	421	2004

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