Nicolas Chopin
Nicolas Chopin
Professor of Statistics, CREST (ENSAE)
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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
A sequential particle filter method for static models
N Chopin
Biometrika 89 (3), 539-552, 2002
Central limit theorem for sequential Monte Carlo methods and its application to Bayesian inference
N Chopin
The Annals of Statistics 32 (6), 2385-2411, 2004
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
On particle methods for parameter estimation in state-space models
N Kantas, A Doucet, SS Singh, J Maciejowski, N Chopin
Statistical science 30 (3), 328-351, 2015
Theory of Probability revisited (with discussion)
C Robert, N Chopin, J Rousseau
Statist. Science 24 (2), 141-172, 2009
Control functionals for Monte Carlo integration
CJ Oates, M Girolami, N Chopin
Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2017
Fast simulation of truncated Gaussian distributions
N Chopin
Statistics and Computing 21 (2), 275-288, 2011
Sequential quasi monte carlo
M Gerber, N Chopin
Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2015
On particle Gibbs sampling
N Chopin, SS Singh
Bernoulli 21 (3), 1855-1883, 2015
Properties of nested sampling
N Chopin, CP Robert
Biometrika 97 (3), 741-755, 2010
Expectation propagation for likelihood-free inference
S Barthelmé, N Chopin
Journal of the American Statistical Association 109 (505), 315-333, 2014
Sequential Monte Carlo on large binary sampling spaces
C Schäfer, N Chopin
Statistics and Computing 23 (2), 163-184, 2013
Dynamic detection of change points in long time series
N Chopin
Annals of the Institute of Statistical Mathematics 59 (2), 349-366, 2007
Expectation propagation as a way of life: A framework for Bayesian inference on partitioned data
A Gelman, A Vehtari, P Jylänki, T Sivula, D Tran, S Sahai, P Blomstedt, ...
arXiv preprint arXiv:1412.4869, 2017
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
Modeling time series of animal behavior by means of a latent‐state model with feedback
W Zucchini, D Raubenheimer, IL MacDonald
Biometrics 64 (3), 807-815, 2008
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
Inference and model choice for sequentially ordered hidden Markov models
N Chopin
Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2007
Parameter inference for stochastic kinetic models of bacterial gene regulation: a Bayesian approach to systems biology
DJ Wilkinson
Proceedings of 9th Valencia International Meeting on Bayesian Statistics …, 2010
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