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 SinghTibra Foundation Chair in Mathematical Sciences, School of Mathematics, University of WollongongVerified email at uow.edu.au
Pierre Del MoralResearch Director, INRIA Bordeaux - Sud OuestVerified email at inria.fr
Adam M. JohansenUniversity of WarwickVerified email at warwick.ac.uk
George (Yorgos) DeligiannidisProfessor of Statistics, University of OxfordVerified email at stats.ox.ac.uk
Simon GodsillUniversity of CambridgeVerified email at eng.cam.ac.uk
Ajay JasraProfessor of Data Science, The Chinese University of Hong Kong, ShenzhenVerified email at cuhk.edu.cn
Neil GordonDefence Science and Technology GroupVerified email at ieee.org
Valentin De BortoliGoogle DeepMind, LondonVerified email at google.com
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
Chris HolmesVerified email at stats.ox.ac.uk
François CaronUniversity of OxfordVerified email at stats.ox.ac.uk
Soufiane HayouSimons Institute for the Theory of Computing, UC Berkeley | PhD @ University of OxfordVerified email at berkeley.edu
Emilien DupontResearch Scientist, DeepMindVerified email at stats.ox.ac.uk
Kevin MurphyResearch Scientist, GoogleVerified email at google.com
Mike WestDuke UniversityVerified email at nc.rr.com
James ThorntonApple | University of OxfordVerified email at apple.com
Jeremy HengAssistant Professor of Statistics, ESSEC Business SchoolVerified email at essec.edu

Arnaud Doucet

Google DeepMind

Verified email at google.com - Homepage

Computational Statistics Machine Learning Monte Carlo methods


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Sequential Monte Carlo Methods in Practice A Doucet, N De Freitas, N Gordon Sequential monte carlo methods in practice, 2001	10699	2001
On sequential Monte Carlo sampling methods for Bayesian filtering A Doucet, S Godsill, C Andrieu Statistics and computing 10, 197-208, 2000	6668	2000
An introduction to MCMC for machine learning C Andrieu, N De Freitas, A Doucet, MI Jordan Machine learning 50, 5-43, 2003	3721	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	2871	2011
Particle Markov chain Monte Carlo methods C Andrieu, A Doucet, R Holenstein Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2010	2730	2010
The unscented particle filter R Van Der Merwe, A Doucet, N De Freitas, EA Wan Advances in Neural Information Processing Systems, 2000	2661	2000
Sequential Monte Carlo samplers P Del Moral, A Doucet, A Jasra Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2006	2257	2006
Rao-Blackwellised particle filtering for dynamic Bayesian networks A Doucet, N De Freitas, K Murphy, S Russell UAI 2000, 2000	2129*	2000
An introduction to sequential Monte Carlo methods A Doucet, N De Freitas, N Gordon Sequential Monte Carlo methods in practice, 3-14, 2001	1742	2001
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	1677	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	1375	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	1143	2001
On sequential simulation-based methods for Bayesian filtering A Doucet Technical Report CUED/F-INFENG/TR.310 Cambridge University, 1998	1065	1998
Fast computation of Wasserstein barycenters M Cuturi, A Doucet Proceedings of the 31st International Conference on Machine Learning, 685-693, 2014	901	2014
Augmented neural ODEs E Dupont, A Doucet, Y Teh Advances in Neural Information Processing Systems 32 (NIPS 2019) 32 (2019), 2019	758	2019
Monte Carlo smoothing for nonlinear time series SJ Godsill, A Doucet, M West Journal of the american statistical association, 2004	752	2004
An adaptive sequential Monte Carlo method for approximate Bayesian computation P Del Moral, A Doucet, A Jasra Statistics and computing 22, 1009-1020, 2012	634	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	581	2015
Maintaining multi-modality through mixture tracking J Vermaak, A Doucet, P Patrick International Conference on Computer Vision, 1110, 2003	564	2003
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	470	2003

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