Pierre Latouche 个人学术档案

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Charles BouveyronProfessor of Statistics & AI, Director of Institut 3IA Côte d'Azur, Inria, Université Côte d'Azur在 inria.fr 的电子邮件经过验证
Christophe AmbroiseProfessor of Statistics, Université d'Evry Val d'Essonne在 univ-evry.fr 的电子邮件经过验证
Fabrice RossiProfessor of Data Science, CEREMADE, Université Paris Dauphine PSL在 dauphine.psl.eu 的电子邮件经过验证
Stéphane ROBINSorbonne université在 sorbonne-universite.fr 的电子邮件经过验证
Pierre-Alexandre MatteiResearch scientist, Inria在 inria.fr 的电子邮件经过验证
Etienne CômeGustave Eiffel University在 univ-eiffel.fr 的电子邮件经过验证
Nial FrielProfessor of Statistics, University College Dublin, COSTNET CA15109在 ucd.ie 的电子邮件经过验证
Julien ChiquetUniversité Paris-Saclay, INRAE, AgroParisTech在 inrae.fr 的电子邮件经过验证
Nicolas JouvinResearch scientist, INRAE, MIA-Paris Laboratory在 inrae.fr 的电子邮件经过验证
Arthur LeroyThe University of Manchester在 manchester.ac.uk 的电子邮件经过验证
Servane GeyUniversité de Paris在 u-paris.fr 的电子邮件经过验证
Yacine JerniteResearch Scientist, HuggingFace在 cs.nyu.edu 的电子邮件经过验证
Jason WyseAssistant Professor在 tcd.ie 的电子邮件经过验证
César DucruetCentre National de la Recherche Scientifique (CNRS)在 economix.fr 的电子邮件经过验证
Benjamin GuedjInria and University College London (UCL)在 inria.fr 的电子邮件经过验证
Pierre LinchampsPostdoctoral fellow在 mnhn.fr 的电子邮件经过验证
Raphaël CornetteMuséum National d'Histoire Naturelle-UMR 7205 ISYEB在 mnhn.fr 的电子邮件经过验证
Raphaël HanonUniversity of the Witwatersrand, Johannesburg在 edu.mnhn.fr 的电子邮件经过验证
Riccardo RastelliAssistant Professor, University College Dublin在 ucd.ie 的电子邮件经过验证
Laurent BergéUniversité de Bordeaux在 u-bordeaux.fr 的电子邮件经过验证

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Pierre Latouche

Laboratoire LMBP, Université Clermont Auvergne

在 math.cnrs.fr 的电子邮件经过验证 - 首页

Statistical learning on networks texts and heterogenous data Statistical learning in high dimensions Statistical learning wi


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
Overlapping stochastic block models with application to the french political blogosphere P Latouche, E Birmelé, C Ambroise	245	2011
Variational Bayesian inference and complexity control for stochastic block models P Latouche, E Birmele, C Ambroise Statistical Modelling 12 (1), 93-115, 2012	203	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	137	2015
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	63	2018
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	53	2017
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	50	2016
Multiple change points detection and clustering in dynamic networks M Corneli, P Latouche, F Rossi Statistics and Computing 28, 989-1007, 2018	38	2018
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	34	2016
Bayesian methods for graph clustering P Latouche, E Birmelé, C Ambroise Advances in Data Analysis, Data Handling and Business Intelligence …, 2010	34	2010
Graphs in machine learning. An introduction. P Latouche, F Rossi ESANN, 2015	33	2015
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	32	2014
Bayesian variable selection for globally sparse probabilistic PCA C Bouveyron, P Latouche, PA Mattei	31	2018
The dynamic random subgraph model for the clustering of evolving networks R Zreik, P Latouche, C Bouveyron Computational Statistics 32, 501-533, 2017	25	2017
Exact dimensionality selection for Bayesian PCA C Bouveyron, P Latouche, PA Mattei Scandinavian Journal of Statistics 47 (1), 196-211, 2020	23	2020
Model selection in overlapping stochastic block models P Latouche, E Birmelé, C Ambroise	22	2014
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	21	2018
Overlapping stochastic block models P Latouche, E Birmelé, C Ambroise arXiv preprint arXiv:0910.2098, 2009	21	2009
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, 1-14, 2016	20	2016
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	20	2013
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	18	2021

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