Folgen
Pierre Latouche
Pierre Latouche
Laboratoire MAP5, Université de Paris
Bestätigte E-Mail-Adresse bei math.cnrs.fr - Startseite
Titel
Zitiert von
Zitiert von
Jahr
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
2082011
Variational Bayesian inference and complexity control for stochastic block models
P Latouche, E Birmele, C Ambroise
Statistical Modelling 12 (1), 93-115, 2012
1772012
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
1052015
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
482017
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
442018
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
342016
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
342014
Bayesian methods for graph clustering
P Latouche, E Birmelé, C Ambroise
Advances in Data Analysis, Data Handling and Business Intelligence, 229-239, 2009
342009
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
282016
Multiple change points detection and clustering in dynamic networks
M Corneli, P Latouche, F Rossi
Statistics and Computing 28 (5), 989-1007, 2018
272018
The dynamic random subgraph model for the clustering of evolving networks
R Zreik, P Latouche, C Bouveyron
Computational Statistics 32 (2), 501-533, 2017
252017
Graphs in machine learning: an introduction
P Latouche, F Rossi
European Symposium on Artificial Neural Networks, Computational Intelligence …, 2015
252015
Bayesian variable selection for globally sparse probabilistic PCA
C Bouveyron, P Latouche, PA Mattei
Electronic Journal of Statistics 12 (2), 3036-3070, 2018
242018
Model selection in overlapping stochastic block models
P Latouche, E Birmelé, C Ambroise
Electronic journal of statistics 8 (1), 762-794, 2014
202014
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
202013
Overlapping stochastic block models
P Latouche, E Birmelé, C Ambroise
arXiv preprint arXiv:0910.2098, 2009
192009
Choosing the number of groups in a latent stochastic blockmodel for dynamic networks
R Rastelli, P Latouche, N Friel
Network Science 6 (4), 469-493, 2018
162018
Goodness of fit of logistic models for random graphs
P Latouche, S Robin, S Ouadah
arXiv preprint arXiv:1508.00286, 2015
152015
Exact dimensionality selection for Bayesian PCA
C Bouveyron, P Latouche, PA Mattei
Scandinavian Journal of Statistics 47 (1), 196-211, 2020
142020
Block modelling in dynamic networks with non-homogeneous poisson processes and exact ICL
M Corneli, P Latouche, F Rossi
Social Network Analysis and Mining 6 (1), 1-14, 2016
142016
Das System kann den Vorgang jetzt nicht ausführen. Versuchen Sie es später erneut.
Artikel 1–20