Nicolas Chopin 个人学术档案

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	总计	2019 年至今
引用	11157	6402
h 指数	27	22
i10 指数	45	34

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Omiros PapaspiliopoulosBocconi在 unibocconi.it 的电子邮件经过验证
Sara MartinoNorwegian University of Science and Technology在 ntnu.no 的电子邮件经过验证
Håvard RueKing Abdullah University of Science and Technology在 kaust.edu.sa 的电子邮件经过验证
Christian RobertUniversité Paris Dauphine, PSL & University of Warwick在 ceremade.dauphine.fr 的电子邮件经过验证
Sumeetpal Sidhu SinghTibra Foundation Chair in Mathematical Sciences, School of Mathematics, University of Wollongong在 uow.edu.au 的电子邮件经过验证
Pierre AlquierESSEC Business School在 essec.edu 的电子邮件经过验证
Pierre E. JacobESSEC Business School在 essec.edu 的电子邮件经过验证
Simon BarthelméCNRS Research Fellow, Gipsa-lab在 gipsa-lab.fr 的电子邮件经过验证
Arnaud DoucetProfessor of Statistics, University of Oxford & Research Scientist, Google DeepMind在 stats.ox.ac.uk 的电子邮件经过验证
James RidgwayCapital Fund Management在 cfm.fr 的电子邮件经过验证
Judith RousseauUniversity of oxford在 stats.ox.ac.uk 的电子邮件经过验证
Mark GirolamiUniversity of Cambridge在 cam.ac.uk 的电子邮件经过验证
Christophe AndrieuProfessor of Statistics, University of Bristol在 bristol.ac.uk 的电子邮件经过验证
Chris. J. OatesNewcastle University在 ncl.ac.uk 的电子邮件经过验证
Nikolas KantasDept. of Mathematics, Imperial College London在 imperial.ac.uk 的电子邮件经过验证
Jan MaciejowskiUniversity of Cambridge在 cam.ac.uk 的电子邮件经过验证
Nick WhiteleyUniversity of Bristol在 bristol.ac.uk 的电子邮件经过验证
Alexander BuchholzAmazon在 amazon.de 的电子邮件经过验证
Robin J. RyderCEREMADE, Université Paris Dauphine在 ceremade.dauphine.fr 的电子邮件经过验证
LELIEVRE, TONYProfessor of Applied Mathematics, Ecole des Ponts ParisTech and INRIA在 cermics.enpc.fr 的电子邮件经过验证

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Nicolas Chopin

Professor of Statistics, ENSAE (Institut Polytechnique de Paris)

在 ensae.fr 的电子邮件经过验证 - 首页

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


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
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	5609	2009
A sequential particle filter method for static models N Chopin Biometrika 89 (3), 539-552, 2002	823	2002
Central limit theorem for sequential Monte Carlo methods and its application to Bayesian inference N Chopin	566	2004
On particle methods for parameter estimation in state-space models N Kantas, A Doucet, SS Singh, J Maciejowski, N Chopin	541	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	508	2013
An introduction to sequential Monte Carlo N Chopin, O Papaspiliopoulos Springer, 2020	338	2020
On the properties of variational approximations of Gibbs posteriors P Alquier, J Ridgway, N Chopin Journal of Machine Learning Research 17 (236), 1-41, 2016	252	2016
Control functionals for Monte Carlo integration CJ Oates, M Girolami, N Chopin Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2017	241	2017
Theory of Probability revisited (with discussion) C Robert, N Chopin, J Rousseau Statist. Science 24 (2), 141-172, 2009	236*	2009
On particle Gibbs sampling N Chopin, SS Singh	171	2015
Sequential quasi monte carlo M Gerber, N Chopin Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2015	160	2015
Fast simulation of truncated Gaussian distributions N Chopin Statistics and Computing 21, 275-288, 2011	157	2011
A Bayesian information criterion for singular models M Drton, M Plummer Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2017	149	2017
Properties of nested sampling N Chopin, CP Robert Biometrika 97 (3), 741-755, 2010	136	2010
Sequential Monte Carlo on large binary sampling spaces C Schäfer, N Chopin Statistics and Computing 23, 163-184, 2013	117	2013
Expectation propagation for likelihood-free inference S Barthelmé, N Chopin Journal of the American Statistical Association 109 (505), 315-333, 2014	116	2014
Negative association, ordering and convergence of resampling methods M Gerber, N Chopin, N Whiteley The Annals of Statistics 47 (4), 2236-2260, 2019	88	2019
Leave Pima Indians alone: binary regression as a benchmark for Bayesian computation N Chopin, J Ridgway	86	2017
Dynamic detection of change points in long time series N Chopin Annals of the Institute of Statistical Mathematics 59 (2), 349-366, 2007	85	2007
Bayesian inference and state number determination for hidden Markov models: an application to the information content of the yield curve about inflation N Chopin, F Pelgrin Journal of Econometrics 123 (2), 327-344, 2004	55	2004

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