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
Pierre Del MoralResearch Director, INRIA Bordeaux - Sud OuestVerified email at inria.fr
Sumeetpal Sidhu SinghTibra Foundation Chair in Mathematical Sciences, School of Mathematics, University of WollongongVerified email at uow.edu.au
Adam M. JohansenUniversity of WarwickVerified email at warwick.ac.uk
Simon GodsillUniversity of CambridgeVerified email at eng.cam.ac.uk
George DeligiannidisAssociate Professor in Statistics, University of OxfordVerified email at stats.ox.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
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
Valentin De BortoliGoogle DeepMind, LondonVerified email at google.com
Soufiane HayouSimons Institute for the Theory of Computing, UC Berkeley (On Leave from NUS)Verified email at berkeley.edu
Mike WestDuke UniversityVerified email at nc.rr.com
Emilien DupontResearch Scientist, DeepMindVerified email at stats.ox.ac.uk
Kevin MurphyResearch Scientist, GoogleVerified email at google.com
Vikram KrishnamurthyProfessor, Cornell UniversityVerified email at cornell.edu
Anthony LeeSchool of Mathematics, University 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


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Sequential Monte Carlo Methods in Practice A Doucet, N De Freitas, N Gordon Sequential monte carlo methods in practice, 2001	10460	2001
On sequential Monte Carlo sampling methods for Bayesian filtering A Doucet, S Godsill, C Andrieu Statistics and computing 10, 197-208, 2000	6467	2000
An introduction to MCMC for machine learning C Andrieu, N De Freitas, A Doucet, MI Jordan Machine learning 50, 5-43, 2003	3433	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	2665	2011
The unscented particle filter R Van Der Merwe, A Doucet, N De Freitas, EA Wan Advances in Neural Information Processing Systems, 2000	2576	2000
Particle Markov chain Monte Carlo methods C Andrieu, A Doucet, R Holenstein Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2010	2549	2010
Sequential Monte Carlo samplers P Del Moral, A Doucet, A Jasra Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2006	2032	2006
Rao-Blackwellised particle filtering for dynamic Bayesian networks A Doucet, N De Freitas, K Murphy, S Russell UAI 2000, 2000	2021*	2000
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	1622	2005
An introduction to sequential Monte Carlo methods A Doucet, N De Freitas, N Gordon Sequential Monte Carlo methods in practice, 3-14, 2001	1568	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	1319	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	1106	2001
On sequential simulation-based methods for Bayesian filtering A Doucet Technical Report CUED/F-INFENG/TR.310 Cambridge University, 1998	1058	1998
Fast computation of Wasserstein barycenters M Cuturi, A Doucet Proceedings of the 31st International Conference on Machine Learning, 685-693, 2014	770	2014
Monte Carlo smoothing for nonlinear time series SJ Godsill, A Doucet, M West Journal of the american statistical association, 2004	702	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	578	2012
Maintaining multi-modality through mixture tracking J Vermaak, A Doucet, P Patrick International Conference on Computer Vision, 1110, 2003	566	2003
Augmented neural ODEs E Dupont, A Doucet, Y Teh Advances in Neural Information Processing Systems 32 (NIPS 2019) 32 (2019), 2019	539	2019
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	510	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	457	2003

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