Overlapping stochastic block models with application to the french political blogosphere P Latouche, E Birmelé, C Ambroise The Annals of Applied Statistics 5 (1), 309-336, 2011 | 139 | 2011 |

Variational Bayesian inference and complexity control for stochastic block models P Latouche, E Birmele, C Ambroise Statistical Modelling 12 (1), 93-115, 2012 | 120 | 2012 |

Model selection and clustering in stochastic block models based on the exact integrated complete data likelihood E Côme, P Latouche Statistical Modelling 15 (6), 564-589, 2015 | 58 | 2015 |

Inferring structure in bipartite networks using the latent blockmodel and exact ICL J Wyse, N Friel, P Latouche Network Science 5 (1), 45-69, 2017 | 32 | 2017 |

The stochastic topic block model for the clustering of vertices in networks with textual edges C Bouveyron, P Latouche, R Zreik Statistics and Computing 28 (1), 11-31, 2018 | 28 | 2018 |

The random subgraph model for the analysis of an ecclesiastical network in Merovingian Gaul Y Jernite, P Latouche, C Bouveyron, P Rivera, L Jegou, S Lamassé The Annals of Applied Statistics 8 (1), 377-405, 2014 | 28 | 2014 |

Bayesian methods for graph clustering P Latouche, E Birmelé, C Ambroise Advances in Data Analysis, Data Handling and Business Intelligence, 229-239, 2009 | 27 | 2009 |

Bayesian model averaging of stochastic block models to estimate the graphon function and motif frequencies in a w-graph model P Latouche, S Robin arXiv preprint arXiv:1310.6150, 2013 | 19 | 2013 |

The dynamic random subgraph model for the clustering of evolving networks R Zreik, P Latouche, C Bouveyron Computational Statistics 32 (2), 501-533, 2017 | 18 | 2017 |

Overlapping stochastic block models P Latouche, E Birmelé, C Ambroise arXiv preprint arXiv:0910.2098, 2009 | 17 | 2009 |

Model selection in overlapping stochastic block models P Latouche, E Birmelé, C Ambroise Electronic journal of statistics 8 (1), 762-794, 2014 | 15 | 2014 |

Exact ICL maximization in a non-stationary temporal extension of the stochastic block model for dynamic networks M Corneli, P Latouche, F Rossi Neurocomputing 192, 81-91, 2016 | 13 | 2016 |

Combining a relaxed EM algorithm with Occam’s razor for Bayesian variable selection in high-dimensional regression P Latouche, PA Mattei, C Bouveyron, J Chiquet Journal of Multivariate Analysis 146, 177-190, 2016 | 13 | 2016 |

Variational Bayes model averaging for graphon functions and motif frequencies inference in W-graph models P Latouche, S Robin Statistics and Computing 26 (6), 1173-1185, 2016 | 12 | 2016 |

Multiple change points detection and clustering in dynamic networks M Corneli, P Latouche, F Rossi Statistics and Computing 28 (5), 989-1007, 2018 | 11 | 2018 |

Bayesian variable selection for globally sparse probabilistic PCA C Bouveyron, P Latouche, PA Mattei arXiv preprint arXiv:1605.05918, 2016 | 11 | 2016 |

Goodness of fit of logistic models for random graphs P Latouche, S Robin, S Ouadah arXiv preprint arXiv:1508.00286, 2015 | 11 | 2015 |

Modèles de graphes aléatoires à structure cachée pour l'analyse des réseaux P Latouche | 11 | 2010 |

Graphs in machine learning: an introduction P Latouche, F Rossi European Symposium on Artificial Neural Networks, Computational Intelligence …, 2015 | 10 | 2015 |

Globally sparse probabilistic PCA PA Mattei, C Bouveyron, P Latouche Artificial Intelligence and Statistics, 976-984, 2016 | 9 | 2016 |