An entropy criterion for assessing the number of clusters in a mixture model G Celeux, G Soromenho Journal of classification 13 (2), 195-212, 1996 | 1461 | 1996 |

Assessing a mixture model for clustering with the integrated completed likelihood C Biernacki, G Celeux, G Govaert IEEE transactions on pattern analysis and machine intelligence 22 (7), 719-725, 2000 | 1373 | 2000 |

Gaussian parsimonious clustering models G Celeux, G Govaert Pattern recognition 28 (5), 781-793, 1995 | 998 | 1995 |

A classification EM algorithm for clustering and two stochastic versions G Celeux, G Govaert Computational statistics & Data analysis 14 (3), 315-332, 1992 | 955 | 1992 |

Deviance information criteria for missing data models G Celeux, F Forbes, CP Robert, DM Titterington Bayesian analysis 1 (4), 651-673, 2006 | 851 | 2006 |

Computational and inferential difficulties with mixture posterior distributions G Celeux, M Hurn, CP Robert Journal of the American Statistical Association 95 (451), 957-970, 2000 | 734 | 2000 |

The SEM algorithm: a probabilistic teacher algorithm derived from the EM algorithm for the mixture problem G Celeux Computational statistics quarterly 2, 73-82, 1985 | 696 | 1985 |

Choosing starting values for the EM algorithm for getting the highest likelihood in multivariate Gaussian mixture models C Biernacki, G Celeux, G Govaert Computational Statistics & Data Analysis 41 (3-4), 561-575, 2003 | 621 | 2003 |

EM procedures using mean field-like approximations for Markov model-based image segmentation G Celeux, F Forbes, N Peyrard Pattern recognition 36 (1), 131-144, 2003 | 395 | 2003 |

Classification automatique des données:[environnement statistique et informatique] G Celeux, E Diday, G Govaert, Y Lechevallier, H Ralambondrainy Bordas, 1989 | 295 | 1989 |

Combining mixture components for clustering JP Baudry, AE Raftery, G Celeux, K Lo, R Gottardo Journal of computational and graphical statistics 19 (2), 332-353, 2010 | 267 | 2010 |

Inference in model-based cluster analysis H Bensmail, G Celeux, AE Raftery, CP Robert statistics and Computing 7 (1), 1-10, 1997 | 266 | 1997 |

Regularized Gaussian discriminant analysis through eigenvalue decomposition H Bensmail, G Celeux Journal of the American statistical Association 91 (436), 1743-1748, 1996 | 230 | 1996 |

Bayesian estimation of hidden Markov chains: A stochastic implementation CP Robert, G Celeux, J Diebolt Statistics & Probability Letters 16 (1), 77-83, 1993 | 219 | 1993 |

Variable selection for clustering with Gaussian mixture models C Maugis, G Celeux, ML Martin‐Magniette Biometrics 65 (3), 701-709, 2009 | 218 | 2009 |

Stochastic versions of the EM algorithm: an experimental study in the mixture case G Celeux, D Chauveau, J Diebolt Journal of statistical computation and simulation 55 (4), 287-314, 1996 | 217 | 1996 |

Model-based cluster and discriminant analysis with the MIXMOD software C Biernacki, G Celeux, G Govaert, F Langrognet Computational Statistics & Data Analysis 51 (2), 587-600, 2006 | 202 | 2006 |

An improvement of the NEC criterion for assessing the number of clusters in a mixture model C Biernacki, G Celeux, G Govaert Pattern Recognition Letters 20 (3), 267-272, 1999 | 178 | 1999 |

A stochastic approximation type EM algorithm for the mixture problem G Celeux, J Diebolt Stochastics: An International Journal of Probability and Stochastic …, 1992 | 172 | 1992 |

A component-wise EM algorithm for mixtures G Celeux, S Chrétien, F Forbes, A Mkhadri Journal of Computational and Graphical Statistics 10 (4), 697-712, 2001 | 168 | 2001 |