Pierre Latouche
Pierre Latouche
Laboratoire MAP5, Université Paris Descartes
Verified email at math.cnrs.fr - Homepage
TitleCited byYear
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
1392011
Variational Bayesian inference and complexity control for stochastic block models
P Latouche, E Birmele, C Ambroise
Statistical Modelling 12 (1), 93-115, 2012
1202012
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
582015
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
322017
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
282018
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
282014
Bayesian methods for graph clustering
P Latouche, E Birmelé, C Ambroise
Advances in Data Analysis, Data Handling and Business Intelligence, 229-239, 2009
272009
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
192013
The dynamic random subgraph model for the clustering of evolving networks
R Zreik, P Latouche, C Bouveyron
Computational Statistics 32 (2), 501-533, 2017
182017
Overlapping stochastic block models
P Latouche, E Birmelé, C Ambroise
arXiv preprint arXiv:0910.2098, 2009
172009
Model selection in overlapping stochastic block models
P Latouche, E Birmelé, C Ambroise
Electronic journal of statistics 8 (1), 762-794, 2014
152014
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
132016
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
132016
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
122016
Multiple change points detection and clustering in dynamic networks
M Corneli, P Latouche, F Rossi
Statistics and Computing 28 (5), 989-1007, 2018
112018
Bayesian variable selection for globally sparse probabilistic PCA
C Bouveyron, P Latouche, PA Mattei
arXiv preprint arXiv:1605.05918, 2016
112016
Goodness of fit of logistic models for random graphs
P Latouche, S Robin, S Ouadah
arXiv preprint arXiv:1508.00286, 2015
112015
Modèles de graphes aléatoires à structure cachée pour l'analyse des réseaux
P Latouche
112010
Graphs in machine learning: an introduction
P Latouche, F Rossi
European Symposium on Artificial Neural Networks, Computational Intelligence …, 2015
102015
Globally sparse probabilistic PCA
PA Mattei, C Bouveyron, P Latouche
Artificial Intelligence and Statistics, 976-984, 2016
92016
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