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
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 HayouDepartment of Mathematics, National University of SingaporeVerified email at nus.edu.sg
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	10388	2001
On sequential Monte Carlo sampling methods for Bayesian filtering A Doucet, S Godsill, C Andrieu Statistics and computing 10, 197-208, 2000	6414	2000
An introduction to MCMC for machine learning C Andrieu, N De Freitas, A Doucet, MI Jordan Machine learning 50, 5-43, 2003	3393	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	2624	2011
The unscented particle filter R Van Der Merwe, A Doucet, N De Freitas, EA Wan Advances in Neural Information Processing Systems, 2000	2568	2000
Particle Markov chain Monte Carlo methods C Andrieu, A Doucet, R Holenstein Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2010	2515	2010
Rao-Blackwellised particle filtering for dynamic Bayesian networks A Doucet, N De Freitas, K Murphy, S Russell UAI 2000, 2000	2001*	2000
Sequential Monte Carlo samplers P Del Moral, A Doucet, A Jasra Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2006	1992	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	1611	2005
An introduction to sequential Monte Carlo methods A Doucet, N De Freitas, N Gordon Sequential Monte Carlo methods in practice, 3-14, 2001	1549	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	1309	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	1101	2001
On sequential simulation-based methods for Bayesian filtering A Doucet Technical Report CUED/F-INFENG/TR.310 Cambridge University, 1998	1055	1998
Fast computation of Wasserstein barycenters M Cuturi, A Doucet Proceedings of the 31st International Conference on Machine Learning, 685-693, 2014	742	2014
Monte Carlo smoothing for nonlinear time series SJ Godsill, A Doucet, M West Journal of the american statistical association, 2004	691	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	567	2012
Maintaining multi-modality through mixture tracking J Vermaak, A Doucet, P Patrick International Conference on Computer Vision, 1110, 2003	564	2003
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	502	2015
Augmented neural ODEs E Dupont, A Doucet, Y Teh Advances in Neural Information Processing Systems 32 (NIPS 2019) 32 (2019), 2019	501	2019
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	456	2003

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