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2020 – today
- 2023
[j19]Dingge Liang
, Marco Corneli, Charles Bouveyron, Pierre Latouche:
The graph embedded topic model. Neurocomputing 562: 126900 (2023)- [j18]Arthur Leroy, Pierre Latouche, Benjamin Guedj, Servane Gey:
Cluster-Specific Predictions with Multi-Task Gaussian Processes. J. Mach. Learn. Res. 24: 5:1-5:49 (2023) - [j17]Rémi Boutin, Charles Bouveyron, Pierre Latouche:
Embedded topics in the stochastic block model. Stat. Comput. 33(5): 95 (2023) - [i6]Rémi Boutin, Pierre Latouche, Charles Bouveyron:
The Deep Latent Position Topic Model for Clustering and Representation of Networks with Textual Edges. CoRR abs/2304.08242 (2023) - 2022
- [j16]Arthur Leroy, Pierre Latouche, Benjamin Guedj, Servane Gey:
MAGMA: inference and prediction using multi-task Gaussian processes with common mean. Mach. Learn. 111(5): 1821-1849 (2022) - [c10]Dingge Liang, Marco Corneli, Charles Bouveyron, Pierre Latouche:
Deep latent position model for node clustering in graphs. ESANN 2022 - [i5]Rémi Boutin, Charles Bouveyron, Pierre Latouche:
Embedded Topics in the Stochastic Block Model. CoRR abs/2209.10097 (2022) - 2021
- [j15]Etienne Côme, Nicolas Jouvin, Pierre Latouche, Charles Bouveyron:
Hierarchical clustering with discrete latent variable models and the integrated classification likelihood. Adv. Data Anal. Classif. 15(4): 957-986 (2021) - [j14]Nicolas Jouvin, Pierre Latouche, Charles Bouveyron, Guillaume Bataillon, Alain Livartowski:
Greedy clustering of count data through a mixture of multinomial PCA. Comput. Stat. 36(1): 1-33 (2021) - [j13]Dingge Liang, Marco Corneli, Charles Bouveyron, Pierre Latouche:
DeepLTRS: A deep latent recommender system based on user ratings and reviews. Pattern Recognit. Lett. 152: 267-274 (2021) - [j12]Nicolas Jouvin, Charles Bouveyron, Pierre Latouche:
A Bayesian Fisher-EM algorithm for discriminative Gaussian subspace clustering. Stat. Comput. 31(4): 44 (2021) - 2020
- [i4]Arthur Leroy, Pierre Latouche, Benjamin Guedj, Servane Gey:
MAGMA: Inference and Prediction with Multi-Task Gaussian Processes. CoRR abs/2007.10731 (2020) - [i3]Arthur Leroy, Pierre Latouche, Benjamin Guedj, Servane Gey:
Cluster-Specific Predictions with Multi-Task Gaussian Processes. CoRR abs/2011.07866 (2020)
2010 – 2019
- 2019
- [j11]Laurent R. Bergé, Charles Bouveyron, Marco Corneli, Pierre Latouche:
The latent topic block model for the co-clustering of textual interaction data. Comput. Stat. Data Anal. 137: 247-270 (2019) - [j10]Marco Corneli, Charles Bouveyron, Pierre Latouche, Fabrice Rossi:
The dynamic stochastic topic block model for dynamic networks with textual edges. Stat. Comput. 29(4): 677-695 (2019) - 2018
- [j9]Riccardo Rastelli, Pierre Latouche, Nial Friel:
Choosing the number of groups in a latent stochastic blockmodel for dynamic networks. Netw. Sci. 6(4): 469-493 (2018) - [j8]Charles Bouveyron, Pierre Latouche, Rawya Zreik:
The stochastic topic block model for the clustering of vertices in networks with textual edges. Stat. Comput. 28(1): 11-31 (2018) - [j7]Marco Corneli, Pierre Latouche, Fabrice Rossi:
Multiple change points detection and clustering in dynamic networks. Stat. Comput. 28(5): 989-1007 (2018) - 2017
- [j6]Rawya Zreik, Pierre Latouche, Charles Bouveyron:
The dynamic random subgraph model for the clustering of evolving networks. Comput. Stat. 32(2): 501-533 (2017) - [j5]Jason Wyse, Nial Friel, Pierre Latouche:
Inferring structure in bipartite networks using the latent blockmodel and exact ICL. Netw. Sci. 5(1): 45-69 (2017) - 2016
- [j4]Marco Corneli, Pierre Latouche, Fabrice Rossi:
Exact ICL maximization in a non-stationary temporal extension of the stochastic block model for dynamic networks. Neurocomputing 192: 81-91 (2016) - [j3]Pierre Latouche, Pierre-Alexandre Mattei, Charles Bouveyron, Julien Chiquet:
Combining a relaxed EM algorithm with Occam's razor for Bayesian variable selection in high-dimensional regression. J. Multivar. Anal. 146: 177-190 (2016) - [j2]Pierre Latouche, Stéphane Robin:
Variational Bayes model averaging for graphon functions and motif frequencies inference in W-graph models. Stat. Comput. 26(6): 1173-1185 (2016) - [j1]Marco Corneli, Pierre Latouche, Fabrice Rossi:
Block modelling in dynamic networks with non-homogeneous Poisson processes and exact ICL. Soc. Netw. Anal. Min. 6(1): 55:1-55:14 (2016) - [c9]Pierre-Alexandre Mattei, Charles Bouveyron, Pierre Latouche:
Globally Sparse Probabilistic PCA. AISTATS 2016: 976-984 - 2015
- [c8]Kevin Mentzer, François-Xavier Dudouet, Dominique Haughton, Pierre Latouche, Fabrice Rossi:
Is the corporate elite disintegrating?: Interlock boards and the Mizruchi hypothesis. ASONAM 2015: 781-786 - [c7]Marco Corneli, Pierre Latouche, Fabrice Rossi:
Modelling time evolving interactions in networks through a non stationary extension of stochastic block models. ASONAM 2015: 1590-1591 - [c6]Marco Corneli, Pierre Latouche, Fabrice Rossi:
Exact ICL maximization in a non-stationary time extension of latent block model for dynamic networks. ESANN 2015 - [c5]Pierre Latouche, Fabrice Rossi:
Graphs in machine learning. An introduction. ESANN 2015 - [c4]Rawya Zreik, Pierre Latouche, Charles Bouveyron:
A State-Space Model for the Dynamic Random Subgraph Model. ESANN 2015 - [i2]Pierre Latouche, Fabrice Rossi:
Graphs in machine learning: an introduction. CoRR abs/1506.06962 (2015) - 2014
- [r1]Pierre Latouche, Etienne Birmelé, Christophe Ambroise:
Overlapping Clustering Methods for Networks. Handbook of Mixed Membership Models and Their Applications 2014: 547-567 - 2013
- [c3]Laetitia Nouedoui, Pierre Latouche:
Bayesian non parametric inference of discrete valued networks. ESANN 2013 - [c2]Fabrice Rossi, Pierre Latouche:
Activity Date Estimation in Timestamped Interaction Networks. ESANN 2013 - [i1]Fabrice Rossi, Pierre Latouche:
Activity date estimation in timestamped interaction networks. CoRR abs/1310.4914 (2013)
2000 – 2009
- 2008
- [c1]Pierre Latouche, Etienne Birmelé, Christophe Ambroise:
Bayesian Methods for Graph Clustering. GfKl 2008: 229-239
Coauthor Index
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