Arnaud Doucet - Google Scholar

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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 SinghReader in Engineering Statistics, Department of Engineering, Cambridge UniversityVerified 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, KAUSTVerified email at kaust.edu.sa
Ba-Ngu VoCurtin UniversityVerified email at curtin.edu.au
François CaronUniversity of OxfordVerified email at stats.ox.ac.uk
George DeligiannidisAssociate Professor in Statistics, University of OxfordVerified email at stats.ox.ac.uk
Neil GordonDefence Science and Technology GroupVerified email at uq.edu.au
Chris HolmesVerified email at stats.ox.ac.uk
Mike WestDuke UniversityVerified email at nc.rr.com
Yee Whye TehProfessor of Statistical Machine Learning, Oxford, Research Scientist, DeepMindVerified email at stats.ox.ac.uk
Anthony LeeSchool of Mathematics, University of BristolVerified email at bristol.ac.uk
M PittKing's College LondonVerified email at kcl.ac.uk
Kevin MurphyResearch Scientist, GoogleVerified email at google.com
Dan CrisanProfessor of Mathematics, Imperial College LondonVerified email at imperial.ac.uk
Marco CuturiGoogle Brain / CREST-ENSAE.Verified email at google.com
Nick WhiteleyUniversity of BristolVerified email at bristol.ac.uk

Arnaud Doucet

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

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

Bayesian Inference Computational Statistics Machine Learning Monte Carlo methods Nonlinear Filtering


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Sequential Monte Carlo Methods in Practice A Doucet, N De Freitas, N Gordon Sequential monte carlo methods in practice, 2001	9202*	2001
On sequential Monte Carlo sampling methods for Bayesian filtering A Doucet, S Godsill, C Andrieu Statistics and computing 10 (3), 197-208, 2000	5593	2000
An introduction to MCMC for machine learning C Andrieu, N De Freitas, A Doucet, MI Jordan Machine learning 50 (1-2), 5-43, 2003	2536	2003
The unscented particle filter R Van Der Merwe, A Doucet, N De Freitas, EA Wan Advances in neural information processing systems, 584-590, 2001	2264	2001
A tutorial on particle filtering and smoothing: Fifteen years later A Doucet, AM Johansen Oxford Handbook of Nonlinear Filtering 12 (656-704), 3, 2011	1956	2011
Particle Markov chain Monte Carlo methods C Andrieu, A Doucet, R Holenstein Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2010	1828	2010
Rao-Blackwellised particle filtering for dynamic Bayesian networks A Doucet, N De Freitas, K Murphy, S Russell UAI 2000, 2000	1484*	2000
Sequential Monte Carlo samplers P Del Moral, A Doucet, A Jasra Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2006	1473	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	1359	2005
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	1138	2002
An introduction to sequential Monte Carlo methods A Doucet, N De Freitas, N Gordon Sequential Monte Carlo methods in practice, 3-14, 2001	1096	2001
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	983	2001
On sequential simulation-based methods for Bayesian filtering A Doucet Technical Report CUED/F-INFENG/TR.310 Cambridge University, 1998	957	1998
Monte Carlo smoothing for nonlinear time series SJ Godsill, A Doucet, M West Journal of the american statistical association, 2004	555	2004
Maintaining multi-modality through mixture tracking J Vermaak, A Doucet, P Patrick International Conference on Computer Vision, 1110, 2003	532	2003
An adaptive sequential Monte Carlo method for approximate Bayesian computation P Del Moral, A Doucet, A Jasra Statistics and Computing 22 (5), 1009-1020, 2012	418	2012
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	405	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	366	2004
Fast computation of Wasserstein barycenters M Cuturi, A Doucet Proceedings of the 31st International Conference on Machine Learning, 685-693, 2014	358	2014
On the utility of graphics cards to perform massively parallel simulation of advanced Monte Carlo methods A Lee, C Yau, MB Giles, A Doucet, CC Holmes Journal of computational and graphical statistics 19 (4), 769-789, 2010	321	2010

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