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Arnaud Doucet
Arnaud Doucet
Professor of Statistics, University of Oxford & Research Scientist, Google DeepMind
Adresse e-mail validée de stats.ox.ac.uk - Page d'accueil
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Année
Sequential Monte Carlo Methods in Practice
A Doucet, N De Freitas, N Gordon
Sequential monte carlo methods in practice, 2001
103842001
On sequential Monte Carlo sampling methods for Bayesian filtering
A Doucet, S Godsill, C Andrieu
Statistics and computing 10, 197-208, 2000
64092000
An introduction to MCMC for machine learning
C Andrieu, N De Freitas, A Doucet, MI Jordan
Machine learning 50, 5-43, 2003
33892003
A tutorial on particle filtering and smoothing: Fifteen years later
A Doucet, AM Johansen
Oxford Handbook of Nonlinear Filtering 12 (656-704), 3, 2011
26222011
The unscented particle filter
R Van Der Merwe, A Doucet, N De Freitas, EA Wan
Advances in Neural Information Processing Systems, 2000
25662000
Particle Markov chain Monte Carlo methods
C Andrieu, A Doucet, R Holenstein
Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2010
25122010
Rao-Blackwellised particle filtering for dynamic Bayesian networks
A Doucet, N De Freitas, K Murphy, S Russell
UAI 2000, 2000
2000*2000
Sequential Monte Carlo samplers
P Del Moral, A Doucet, A Jasra
Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2006
19892006
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
16122005
An introduction to sequential Monte Carlo methods
A Doucet, N De Freitas, N Gordon
Sequential Monte Carlo methods in practice, 3-14, 2001
15492001
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
13092002
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
11012001
On sequential simulation-based methods for Bayesian filtering
A Doucet
Technical Report CUED/F-INFENG/TR.310 Cambridge University, 1998
10551998
Fast computation of Wasserstein barycenters
M Cuturi, A Doucet
Proceedings of the 31st International Conference on Machine Learning, 685-693, 2014
7412014
Monte Carlo smoothing for nonlinear time series
SJ Godsill, A Doucet, M West
Journal of the american statistical association, 2004
6912004
An adaptive sequential Monte Carlo method for approximate Bayesian computation
P Del Moral, A Doucet, A Jasra
Statistics and computing 22, 1009-1020, 2012
5662012
Maintaining multi-modality through mixture tracking
J Vermaak, A Doucet, P Patrick
International Conference on Computer Vision, 1110, 2003
5642003
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
5022015
Augmented neural ODEs
E Dupont, A Doucet, Y Teh
Advances in Neural Information Processing Systems 32 (NIPS 2019) 32 (2019), 2019
4972019
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
4562003
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