Statistical tests to compare motif count exceptionalities. - Stéphane Robin; Sophie Schbath; Vincent Vandewalle (BMC Bioinform., 2007)

Les modèles de mélange, un outil utile pour la classification semi-supervisée. - Vincent Vandewalle (Monde des Util. Anal. Données, 2009)

A predictive deviance criterion for selecting a generative model in semi-supervised classification. - Vincent Vandewalle; Christophe Biernacki; Gilles Celeux; Gérard Govaert (Comput. Stat. Data Anal., 2013)

Mixture of Gaussians for distance estimation with missing data. - Emil Eirola; Amaury Lendasse; Vincent Vandewalle; Christophe Biernacki (Neurocomputing, 2014)

Model-Based Clustering for Conditionally Correlated Categorical Data. - Matthieu Marbac; Christophe Biernacki; Vincent Vandewalle (J. Classif., 2015)

Latent class model with conditional dependency per modes to cluster categorical data. - Matthieu Marbac; Christophe Biernacki; Vincent Vandewalle (Adv. Data Anal. Classif., 2016)

A tractable multi-partitions clustering. - Matthieu Marbac; Vincent Vandewalle (Comput. Stat. Data Anal., 2019)

From industry-wide parameters to aircraft-centric on-flight inference: improving aeronautics performance prediction with machine learning. - Florent Dewez; Benjamin Guedj; Vincent Vandewalle (CoRR, 2020)

An end-to-end data-driven optimisation framework for constrained trajectories. - Florent Dewez; Benjamin Guedj; Arthur Talpaert; Vincent Vandewalle (CoRR, 2020)

Gaussian-Based Visualization of Gaussian and Non-Gaussian-Based Clustering. - Christophe Biernacki; Matthieu Marbac; Vincent Vandewalle (J. Classif., 2021)

Simultaneous Semiparametric Estimation of Clustering and Regression. - Matthieu Marbac; Mohammed Sedki; Christophe Biernacki; Vincent Vandewalle (J. Comput. Graph. Stat., 2022)