Pierre Latouche

According to our database, Pierre Latouche authored at least 32 papers between 2008 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of three.

2023

The graph embedded topic model.

Dingge Liang, Marco Corneli, Charles Bouveyron, Pierre Latouche

Neurocomputing, December, 2023

Embedded topics in the stochastic block model.

Rémi Boutin, Charles Bouveyron, Pierre Latouche

Stat. Comput., October, 2023

Cluster-Specific Predictions with Multi-Task Gaussian Processes.

Arthur Leroy, Pierre Latouche, Benjamin Guedj, Servane Gey

J. Mach. Learn. Res., 2023

The Deep Latent Position Topic Model for Clustering and Representation of Networks with Textual Edges.

Rémi Boutin, Pierre Latouche, Charles Bouveyron

CoRR, 2023

2022

MAGMA: inference and prediction using multi-task Gaussian processes with common mean.

Arthur Leroy, Pierre Latouche, Benjamin Guedj, Servane Gey

Mach. Learn., 2022

Deep latent position model for node clustering in graphs.

Dingge Liang, Marco Corneli, Charles Bouveyron, Pierre Latouche

Proceedings of the 30th European Symposium on Artificial Neural Networks, 2022

2021

A Bayesian Fisher-EM algorithm for discriminative Gaussian subspace clustering.

Nicolas Jouvin, Charles Bouveyron, Pierre Latouche

Stat. Comput., 2021

DeepLTRS: A deep latent recommender system based on user ratings and reviews.

Dingge Liang, Marco Corneli, Charles Bouveyron, Pierre Latouche

Pattern Recognit. Lett., 2021

Greedy clustering of count data through a mixture of multinomial PCA.

Nicolas Jouvin, Pierre Latouche, Charles Bouveyron, Guillaume Bataillon, Alain Livartowski

Comput. Stat., 2021

Hierarchical clustering with discrete latent variable models and the integrated classification likelihood.

Etienne Côme, Nicolas Jouvin, Pierre Latouche, Charles Bouveyron

Adv. Data Anal. Classif., 2021

2020

MAGMA: Inference and Prediction with Multi-Task Gaussian Processes.

Arthur Leroy, Pierre Latouche, Benjamin Guedj, Servane Gey

CoRR, 2020

2019

The dynamic stochastic topic block model for dynamic networks with textual edges.

Marco Corneli, Charles Bouveyron, Pierre Latouche, Fabrice Rossi

Stat. Comput., 2019

The latent topic block model for the co-clustering of textual interaction data.

Laurent R. Bergé, Charles Bouveyron, Marco Corneli, Pierre Latouche

Comput. Stat. Data Anal., 2019

2018

Multiple change points detection and clustering in dynamic networks.

Marco Corneli, Pierre Latouche, Fabrice Rossi

Stat. Comput., 2018

The stochastic topic block model for the clustering of vertices in networks with textual edges.

Charles Bouveyron, Pierre Latouche, Rawya Zreik

Stat. Comput., 2018

Choosing the number of groups in a latent stochastic blockmodel for dynamic networks.

Riccardo Rastelli, Pierre Latouche, Nial Friel

Netw. Sci., 2018

2017

Inferring structure in bipartite networks using the latent blockmodel and exact ICL.

Jason Wyse, Nial Friel, Pierre Latouche

Netw. Sci., 2017

The dynamic random subgraph model for the clustering of evolving networks.

Rawya Zreik, Pierre Latouche, Charles Bouveyron

Comput. Stat., 2017

2016

Block modelling in dynamic networks with non-homogeneous Poisson processes and exact ICL.

Marco Corneli, Pierre Latouche, Fabrice Rossi

Soc. Netw. Anal. Min., 2016

Variational Bayes model averaging for graphon functions and motif frequencies inference in W-graph models.

Pierre Latouche, Stéphane Robin

Stat. Comput., 2016

Combining a relaxed EM algorithm with Occam's razor for Bayesian variable selection in high-dimensional regression.

Pierre Latouche, Pierre-Alexandre Mattei, Charles Bouveyron, Julien Chiquet

J. Multivar. Anal., 2016

Exact ICL maximization in a non-stationary temporal extension of the stochastic block model for dynamic networks.

Marco Corneli, Pierre Latouche, Fabrice Rossi

Neurocomputing, 2016

Globally Sparse Probabilistic PCA.

Pierre-Alexandre Mattei, Charles Bouveyron, Pierre Latouche

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015

A State-Space Model for the Dynamic Random Subgraph Model.

Rawya Zreik, Pierre Latouche, Charles Bouveyron

Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

Graphs in machine learning. An introduction.

Pierre Latouche, Fabrice Rossi

Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

Exact ICL maximization in a non-stationary time extension of latent block model for dynamic networks.

Marco Corneli, Pierre Latouche, Fabrice Rossi

Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

Is the corporate elite disintegrating?: Interlock boards and the Mizruchi hypothesis.

Kevin Mentzer, François-Xavier Dudouet, Dominique Haughton, Pierre Latouche, Fabrice Rossi

Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2015

Modelling time evolving interactions in networks through a non stationary extension of stochastic block models.

Marco Corneli, Pierre Latouche, Fabrice Rossi

Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2015

2014

Overlapping Clustering Methods for Networks.

Pierre Latouche, Etienne Birmelé, Christophe Ambroise

Proceedings of the Handbook of Mixed Membership Models and Their Applications., 2014

2013

Activity Date Estimation in Timestamped Interaction Networks.

Fabrice Rossi, Pierre Latouche

Proceedings of the 21st European Symposium on Artificial Neural Networks, 2013

Bayesian non parametric inference of discrete valued networks.

Laetitia Nouedoui, Pierre Latouche

Proceedings of the 21st European Symposium on Artificial Neural Networks, 2013

2008

Bayesian Methods for Graph Clustering.

Pierre Latouche, Etienne Birmelé, Christophe Ambroise

Proceedings of the Advances in Data Analysis, Data Handling and Business Intelligence, 2008