Nicolas Chopin

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Omiros PapaspiliopoulosBocconiVerified email at unibocconi.it
Sara MartinoNorwegian University of Science and TechnologyVerified email at ntnu.no
Håvard RueKing Abdullah University of Science and TechnologyVerified email at kaust.edu.sa
Christian RobertUniversité Paris Dauphine, PSL & University of WarwickVerified email at ceremade.dauphine.fr
Sumeetpal Sidhu SinghTibra Foundation Chair in Mathematical Sciences, School of Mathematics, University of WollongongVerified email at uow.edu.au
Pierre AlquierESSECVerified email at essec.edu
Pierre E. JacobESSEC Business SchoolVerified email at essec.edu
Simon BarthelméCNRS Research Fellow, Gipsa-labVerified email at gipsa-lab.fr
Arnaud DoucetProfessor of Statistics, University of Oxford & Senior Research Scientist, Google DeepMindVerified email at stats.ox.ac.uk
James RidgwayCapital Fund ManagementVerified email at cfm.fr
Judith RousseauUniversity of oxfordVerified email at stats.ox.ac.uk
Mark GirolamiUniversity of CambridgeVerified email at cam.ac.uk
Nikolas KantasDept. of Mathematics, Imperial College LondonVerified email at imperial.ac.uk
Jan MaciejowskiUniversity of CambridgeVerified email at eng.cam.ac.uk
Chris. J. OatesNewcastle UniversityVerified email at ncl.ac.uk
Christophe AndrieuProfessor of Statistics, University of BristolVerified email at bristol.ac.uk
Nick WhiteleyUniversity of BristolVerified email at bristol.ac.uk
Alexander BuchholzAmazon Music MLVerified email at amazon.de
Robin J. RyderCEREMADE, Université Paris DauphineVerified email at ceremade.dauphine.fr
LELIEVRE, TONYProfessor of Applied Mathematics, Ecole des Ponts ParisTech and INRIAVerified email at cermics.enpc.fr

Nicolas Chopin

Professor of Statistics, ENSAE (Institut Polytechnique de Paris)

Verified email at ensae.fr - Homepage

Statistics Bayesian Stastistics Bayesian Machine Learning Monte Carlo methods Bayesian computation particle filtering


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Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations H Rue, S Martino, N Chopin Journal of the royal statistical society: Series b (statistical methodology …, 2009	4825	2009
A sequential particle filter method for static models N Chopin Biometrika 89 (3), 539-552, 2002	753	2002
Central limit theorem for sequential Monte Carlo methods and its application to Bayesian inference N Chopin	523	2004
On particle methods for parameter estimation in state-space models N Kantas, A Doucet, SS Singh, J Maciejowski, N Chopin	472	2015
SMC²: an efficient algorithm for sequential analysis of state space models N Chopin, PE Jacob, O Papaspiliopoulos Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2013	453*	2013
Control functionals for Monte Carlo integration CJ Oates, M Girolami, N Chopin Journal of the Royal Statistical Society. Series B (Statistical Methodology …, 2017	214	2017
Theory of Probability revisited (with discussion) C Robert, N Chopin, J Rousseau Statist. Science 24 (2), 141-172, 2009	211*	2009
On the properties of variational approximations of Gibbs posteriors P Alquier, J Ridgway, N Chopin The Journal of Machine Learning Research 17 (1), 8374-8414, 2016	178	2016
An introduction to sequential Monte Carlo N Chopin, O Papaspiliopoulos Springer, 2020	166	2020
On particle Gibbs sampling N Chopin, SS Singh	152	2015
Sequential quasi monte carlo M Gerber, N Chopin Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2015	144	2015
Fast simulation of truncated Gaussian distributions N Chopin Statistics and Computing 21, 275-288, 2011	144	2011
Properties of nested sampling N Chopin, CP Robert Biometrika 97 (3), 741-755, 2010	118	2010
A Bayesian information criterion for singular models M Drton, M Plummer, G Claeskens, J Rousseau, CP Robert, T Imai, ... Journal of the Royal Statistical Society. Series B (Statistical Methodology …, 2017	112	2017
Expectation propagation for likelihood-free inference S Barthelmé, N Chopin Journal of the American Statistical Association 109 (505), 315-333, 2014	112	2014
Sequential Monte Carlo on large binary sampling spaces C Schäfer, N Chopin Statistics and Computing 23, 163-184, 2013	108	2013
Dynamic detection of change points in long time series N Chopin Annals of the Institute of Statistical Mathematics 59 (2), 349, 2007	80	2007
Negative association, ordering and convergence of resampling methods M Gerber, N Chopin, N Whiteley The Annals of Statistics 47 (4), 2236-2260, 2019	66	2019
Leave Pima Indians alone: binary regression as a benchmark for Bayesian computation N Chopin, J Ridgway	59	2017
Inference and model choice for sequentially ordered hidden Markov models N Chopin Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2007	54*	2007

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