Modelling time evolving interactions in networks through a non stationary extension of stochastic block models. - Marco Corneli; Pierre Latouche; Fabrice Rossi (ASONAM, 2015)

Exact ICL maximization in a non-stationary time extension of latent block model for dynamic networks. - Marco Corneli; Pierre Latouche; Fabrice Rossi (ESANN, 2015)

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)

Block modelling in dynamic networks with non-homogeneous Poisson processes and exact ICL. - Marco Corneli; Pierre Latouche; Fabrice Rossi (Soc. Netw. Anal. Min., 2016)

Multiple change points detection and clustering in dynamic networks. - Marco Corneli; Pierre Latouche; Fabrice Rossi (Stat. Comput., 2018)

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)

The dynamic stochastic topic block model for dynamic networks with textual edges. - Marco Corneli; Charles Bouveyron; Pierre Latouche; Fabrice Rossi (Stat. Comput., 2019)

From text saliency to linguistic objects: learning linguistic interpretable markers with a multi-channels convolutional architecture. - Laurent Vanni; Marco Corneli; Damon Mayaffre; Frédéric Precioso (CoRR, 2020)

An Optimal Control Approach to Learning in SIDARTHE Epidemic model. - Andrea Zugarini; Enrico Meloni; Alessandro Betti; Andrea Panizza; Marco Corneli; Marco Gori (CoRR, 2020)

Online Graph Dictionary Learning. - Cédric Vincent-Cuaz; Titouan Vayer; Rémi Flamary; Marco Corneli; Nicolas Courty (ICML, 2021)

Semi-relaxed Gromov Wasserstein divergence with applications on graphs. - Cédric Vincent-Cuaz; Rémi Flamary; Marco Corneli; Titouan Vayer; Nicolas Courty (CoRR, 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)

Deep latent position model for node clustering in graphs. - Dingge Liang; Marco Corneli; Charles Bouveyron; Pierre Latouche (ESANN, 2022)

Semi-relaxed Gromov-Wasserstein divergence and applications on graphs. - Cédric Vincent-Cuaz; Rémi Flamary; Marco Corneli; Titouan Vayer; Nicolas Courty (ICLR, 2022)

Template based Graph Neural Network with Optimal Transport Distances. - Cédric Vincent-Cuaz; Rémi Flamary; Marco Corneli; Titouan Vayer; Nicolas Courty (NeurIPS, 2022)

Co-clustering of evolving count matrices with the dynamic latent block model: application to pharmacovigilance. - Giulia Marchello; Audrey Fresse; Marco Corneli; Charles Bouveyron (Stat. Comput., 2022)

Deep dynamic co-clustering of streams of count data: a new online Zip-dLBM. - Giulia Marchello; Marco Corneli; Charles Bouveyron (ESANN, 2023)

Construction d'un graphe de connaissance à partir des annotations manuelles de textes de zoologie antique. - Arnaud Barbe; Molka Tounsi Dhouib; Catherine Faron; Marco Corneli; Arnaud Zucker (IC, 2023)

Gaussian Embedding of Temporal Networks. - Raphaël Romero; Jefrey Lijffijt; Riccardo Rastelli; Marco Corneli; Tijl De Bie (IEEE Access, 2023)

The graph embedded topic model. - Dingge Liang; Marco Corneli; Charles Bouveyron; Pierre Latouche (Neurocomputing, 2023)

Continuous latent position models for instantaneous interactions. - Riccardo Rastelli; Marco Corneli (Netw. Sci., 2023)

A Deep Dynamic Latent Block Model for Co-clustering of Zero-Inflated Data Matrices. - Giulia Marchello; Marco Corneli; Charles Bouveyron (J. Comput. Graph. Stat., 2024)

Deep dynamic co-clustering of count data streams: application to pharmacovigilance. - Giulia Marchello; Alexandre Destere; Marco Corneli; Charles Bouveyron (J. Data Sci. Stat. Vis., 2024)

The multiplex deep latent position model for the clustering of nodes in multiview networks. - Dingge Liang; Marco Corneli; Charles Bouveyron; Pierre Latouche; Junping Yin (Neurocomputing, 2025)

A Bayesian approach for clustering and exact finite-sample model selection in longitudinal data mixtures. - Marco Corneli; Elena Erosheva; Xunlei Qian; Marco Lorenzi (Comput. Stat., 2025)

Clustering by deep latent position model with graph convolutional network. - Dingge Liang; Marco Corneli; Charles Bouveyron; Pierre Latouche (Adv. Data Anal. Classif., 2025)

An in depth look at the Procrustes-Wasserstein distance: properties and barycenters. - Davide Adamo; Marco Corneli; Manon Vuillien; Emmanuelle Vila (CoRR, 2025)