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Pierre Latouche
Pierre Latouche
Laboratoire LMBP, Université Clermont Auvergne, Institut Universitaire de France (IUF)
E-mailová adresa ověřena na: math.cnrs.fr - Domovská stránka
Název
Citace
Citace
Rok
Overlapping stochastic block models with application to the french political blogosphere
P Latouche, E Birmelé, C Ambroise
2552011
Variational Bayesian inference and complexity control for stochastic block models
P Latouche, E Birmele, C Ambroise
Statistical Modelling 12 (1), 93-115, 2012
2112012
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
1422015
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, 11-31, 2018
702018
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
512017
Variational Bayes model averaging for graphon functions and motif frequencies inference in W-graph models
P Latouche, S Robin
Statistics and Computing 26, 1173-1185, 2016
492016
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
382016
Multiple change points detection and clustering in dynamic networks
M Corneli, P Latouche, F Rossi
Statistics and Computing 28, 989-1007, 2018
372018
Bayesian methods for graph clustering
P Latouche, E Birmelé, C Ambroise
Advances in Data Analysis, Data Handling and Business Intelligence …, 2010
352010
Graphs in machine learning: an introduction
P Latouche, F Rossi
European Symposium on Artificial Neural Networks, Computational Intelligence …, 2015
342015
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
342014
Bayesian variable selection for globally sparse probabilistic PCA
C Bouveyron, P Latouche, PA Mattei
322018
Exact dimensionality selection for Bayesian PCA
C Bouveyron, P Latouche, PA Mattei
Scandinavian Journal of Statistics 47 (1), 196-211, 2020
272020
The dynamic random subgraph model for the clustering of evolving networks
R Zreik, P Latouche, C Bouveyron
Computational Statistics 32, 501-533, 2017
272017
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
232018
Model selection in overlapping stochastic block models
P Latouche, E Birmelé, C Ambroise
232014
Overlapping stochastic block models
P Latouche, E Birmelé, C Ambroise
arXiv preprint arXiv:0910.2098, 2009
232009
MAGMA: inference and prediction using multi-task Gaussian processes with common mean
A Leroy, P Latouche, B Guedj, S Gey
Machine Learning 111 (5), 1821-1849, 2022
222022
Hierarchical clustering with discrete latent variable models and the integrated classification likelihood
E Côme, N Jouvin, P Latouche, C Bouveyron
Advances in Data Analysis and Classification 15 (4), 957-986, 2021
222021
Co-clustering of ordinal data via latent continuous random variables and not missing at random entries
M Corneli, C Bouveyron, P Latouche
Journal of Computational and Graphical Statistics 29 (4), 771-785, 2020
202020
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Články 1–20