An improvement of the NEC criterion for assessing the number of clusters in a mixture model. - Christophe Biernacki; Gilles Celeux; Gérard Govaert (Pattern Recognit. Lett., 1999)

Introduction to the Special Section on Video Surveillance. - Robert T. Collins; Christophe Biernacki; Gilles Celeux; Alan J. Lipton; Gérard Govaert; Takeo Kanade (IEEE Trans. Pattern Anal. Mach. Intell., 2000)

Statistical modelling for image retrieval using a biological model of the perceptive colour space. - Anne Guérin-Dugué; Christophe Biernacki; Jeanny Hérault (ICIP (1), 2001)

Choosing starting values for the EM algorithm for getting the highest likelihood in multivariate Gaussian mixture models. - Christophe Biernacki; Gilles Celeux; Gérard Govaert (Comput. Stat. Data Anal., 2003)

Initializing EM using the properties of its trajectories in Gaussian mixtures. - Christophe Biernacki (Stat. Comput., 2004)

Relaxations de la régression logistique : modèles pour l'apprentissage sur une sous-population et la prédiction sur une autre. - Farid Beninel; Christophe Biernacki (DMAS, 2005)

Analyse discriminante sur données binaires lorsque les populations d'apprentissage et de test sont différentes. - Julien Jacques; Christophe Biernacki (DMAS, 2005)

Model-based cluster and discriminant analysis with the MIXMOD software. - Christophe Biernacki; Gilles Celeux; Gérard Govaert; Florent Langrognet (Comput. Stat. Data Anal., 2006)

Le logiciel MIXMOD d'analyse de mélange pour la classification et l'analyse discriminante. - Christophe Biernacki; Gilles Celeux; Anwuli Echenim; Gérard Govaert; Florent Langrognet (Monde des Util. Anal. Données, 2006)

Parameter Setting for Evolutionary Latent Class Clustering. - Damien Tessier; Marc Schoenauer; Christophe Biernacki; Gilles Celeux; Gérard Govaert (ISICA, 2007)

Updating a Logistic Discrimination Rule - Comparing Some Logistic Submodels in Credit-scoring. - Farid Beninel; Christophe Biernacki (ICAART, 2009)

Pourquoi les modèles de mélange pour la classification ? - Christophe Biernacki (Monde des Util. Anal. Données, 2009)

A generative model for rank data based on insertion sort algorithm. - Christophe Biernacki; Julien Jacques (Comput. Stat. Data Anal., 2013)

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)

Simultaneous Gaussian model-based clustering for samples of multiple origins. - Alexandre Lourme; Christophe Biernacki (Comput. Stat., 2013)

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

Rankcluster: An R Package for Clustering Multivariate Partial Rankings. - Julien Jacques; Quentin Grimonprez; Christophe Biernacki (R J., 2014)

Stable and visualizable Gaussian parsimonious clustering models. - Christophe Biernacki; Alexandre Lourme (Stat. Comput., 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)

Variable Clustering in High-Dimensional Linear Regression: The R Package clere. - Loïc Yengo; Julien Jacques; Christophe Biernacki; Mickaël Canouil (R J., 2016)

Model-based clustering of multivariate ordinal data relying on a stochastic binary search algorithm. - Christophe Biernacki; Julien Jacques (Stat. Comput., 2016)

A mixture model-based real-time audio sources classification method. - Maxime Baelde; Christophe Biernacki; Raphael Greff (ICASSP, 2017)

Probability Estimation by an Adapted Genetic Algorithm in Web Insurance. - Anne-Lise Bedenel; Laetitia Jourdan; Christophe Biernacki (LION, 2018)

Relaxing the Identically Distributed Assumption in Gaussian Co-Clustering for High Dimensional Data. - Michael P. B. Gallaugher; Christophe Biernacki; Paul D. McNicholas (CoRR, 2018)

Model-based co-clustering for ordinal data. - Julien Jacques; Christophe Biernacki (Comput. Stat. Data Anal., 2018)

Unifying data units and models in (co-)clustering. - Christophe Biernacki; Alexandre Lourme (Adv. Data Anal. Classif., 2019)

Real-Time monophonic and polyphonic audio classification from power spectra. - Maxime Baelde; Christophe Biernacki; Raphael Greff (Pattern Recognit., 2019)

Target to Source Coordinate-Wise Adaptation of Pre-trained Models. - Luxin Zhang; Pascal Germain; Yacine Kessaci; Christophe Biernacki (ECML/PKDD (1), 2020)

Special issue on "Innovations on model based clustering and classification". - Christophe Biernacki; Luis Angel García-Escudero; Salvatore Ingrassia (Adv. Data Anal. Classif., 2020)

Model-based co-clustering for mixed type data. - Margot Selosse; Julien Jacques; Christophe Biernacki (Comput. Stat. Data Anal., 2020)

Textual data summarization using the Self-Organized Co-Clustering model. - Margot Selosse; Julien Jacques; Christophe Biernacki (Pattern Recognit., 2020)

ordinalClust: An R Package to Analyze Ordinal Data. - Margot Selosse; Julien Jacques; Christophe Biernacki (R J., 2020)

Clustering multilayer graphs with missing nodes. - Guillaume Braun; Hemant Tyagi; Christophe Biernacki (AISTATS, 2021)

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

Interpretable Domain Adaptation for Hidden Subdomain Alignment in the Context of Pre-trained Source Models. - Luxin Zhang; Pascal Germain; Yacine Kessaci; Christophe Biernacki (AAAI, 2022)

An iterative clustering algorithm for the Contextual Stochastic Block Model with optimality guarantees. - Guillaume Braun; Hemant Tyagi; Christophe Biernacki (ICML, 2022)

Interpretable domain adaptation using unsupervised feature selection on pre-trained source models. - Luxin Zhang; Pascal Germain; Yacine Kessaci; Christophe Biernacki (Neurocomputing, 2022)

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

Comparative study of clustering models for multivariate time series from connected medical devices. - Violaine Courrier; Christophe Biernacki; Cristian Preda; Benjamin Vittrant (CoRR, 2023)

Frugal Gaussian clustering of huge imbalanced datasets through a bin-marginal approach. - Filippo Antonazzo; Christophe Biernacki; Christine Keribin (Stat. Comput., 2023)

A Survey on Model-Based Co-Clustering: High Dimension and Estimation Challenges. - Christophe Biernacki; Julien Jacques; Christine Keribin (J. Classif., 2023)

Parameter-wise co-clustering for high-dimensional data. - Michael P. B. Gallaugher; Christophe Biernacki; Paul D. McNicholas (Comput. Stat., 2023)

Model-based clustering with missing not at random data. - Aude Sportisse; Matthieu Marbac; Fabien Laporte; Gilles Celeux; Claire Boyer; Julie Josse; Christophe Biernacki (Stat. Comput., 2024)