Arnaud Doucet

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Coauteurs

Christophe AndrieuProfessor of Statistics, University of BristolAdresse e-mail validée de bristol.ac.uk
Nando de FreitasCIFAR & DeepMindAdresse e-mail validée de google.com
Sumeetpal Sidhu SinghTibra Foundation Chair in Mathematical Sciences, School of Mathematics, University of WollongongAdresse e-mail validée de uow.edu.au
Pierre Del MoralResearch Director, INRIA Bordeaux - Sud OuestAdresse e-mail validée de inria.fr
Adam M. JohansenUniversity of WarwickAdresse e-mail validée de warwick.ac.uk
George (Yorgos) DeligiannidisProfessor of Statistics, University of OxfordAdresse e-mail validée de stats.ox.ac.uk
Simon GodsillUniversity of CambridgeAdresse e-mail validée de eng.cam.ac.uk
Ajay JasraProfessor of Data Science, The Chinese University of Hong Kong, ShenzhenAdresse e-mail validée de cuhk.edu.cn
Neil GordonDefence Science and Technology GroupAdresse e-mail validée de ieee.org
Valentin De BortoliGoogle DeepMind, LondonAdresse e-mail validée de google.com
Yee Whye TehProfessor of Statistical Machine Learning, Oxford, Research Scientist, DeepMindAdresse e-mail validée de stats.ox.ac.uk
Ba-Ngu VoCurtin UniversityAdresse e-mail validée de curtin.edu.au
Chris HolmesAdresse e-mail validée de stats.ox.ac.uk
François CaronUniversity of OxfordAdresse e-mail validée de stats.ox.ac.uk
Soufiane HayouSimons Institute for the Theory of Computing, UC Berkeley | PhD @ University of OxfordAdresse e-mail validée de berkeley.edu
Emilien DupontResearch Scientist, DeepMindAdresse e-mail validée de stats.ox.ac.uk
Kevin MurphyResearch Scientist, GoogleAdresse e-mail validée de google.com
Mike WestDuke UniversityAdresse e-mail validée de nc.rr.com
James ThorntonApple | University of OxfordAdresse e-mail validée de apple.com
Jeremy HengAssistant Professor of Statistics, ESSEC Business SchoolAdresse e-mail validée de essec.edu

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Arnaud Doucet

Google DeepMind

Adresse e-mail validée de google.com - Page d'accueil

Computational Statistics Machine Learning Monte Carlo methods


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Sequential Monte Carlo Methods in Practice A Doucet, N De Freitas, N Gordon Sequential monte carlo methods in practice, 2001	10701	2001
On sequential Monte Carlo sampling methods for Bayesian filtering A Doucet, S Godsill, C Andrieu Statistics and computing 10, 197-208, 2000	6669	2000
An introduction to MCMC for machine learning C Andrieu, N De Freitas, A Doucet, MI Jordan Machine learning 50, 5-43, 2003	3720	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	2874	2011
Particle Markov chain Monte Carlo methods C Andrieu, A Doucet, R Holenstein Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2010	2732	2010
The unscented particle filter R Van Der Merwe, A Doucet, N De Freitas, EA Wan Advances in Neural Information Processing Systems, 2000	2662	2000
Sequential Monte Carlo samplers P Del Moral, A Doucet, A Jasra Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2006	2256	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	1376	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	583	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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