Convergence of an EM-type algorithm for spatial clustering. - Christophe Ambroise; Gérard Govaert (Pattern Recognit. Lett., 1998)

Hierarchical clustering of self-organizing maps for cloud classification. - Christophe Ambroise; Geniève Sèze; Fouad Badran; Sylvie Thiria (Neurocomputing, 2000)

Boosting Mixture Models for Semi-supervised Learning. - Yves Grandvalet; Florence d'Alché-Buc; Christophe Ambroise (ICANN, 2001)

Semi-supervised MarginBoost. - Florence d'Alché-Buc; Yves Grandvalet; Christophe Ambroise (NIPS, 2001)

Feature selection for semisupervised learning applied to image retrieval. - Micheline Najjar; Christophe Ambroise; Jean Pierre Cocquerez (ICIP (2), 2003)

Regularization Methods for Additive Models. - Marta Avalos; Yves Grandvalet; Christophe Ambroise (IDA, 2003)

A Mixture Model Approach for Binned Data Clustering. - Allou Samé; Christophe Ambroise; Gérard Govaert (IDA, 2003)

Image Retrieval Using Mixture Models and EM Algorithm. - Micheline Najjar; Christophe Ambroise; Jean Pierre Cocquerez (SCIA, 2003)

On the Simultaneous Use of Clinical and Microarray Expression Data in the Cluster Analysis of Tissue Samples. - Geoffrey J. McLachlan; Soong Chang; Jess Mar; Christophe Ambroise; Justin Xi Zhu (APBC, 2004)

A Mixture Model-Based On-line CEM Algorithm. - Allou Samé; Gérard Govaert; Christophe Ambroise (IDA, 2005)

Discrimination par modèles additifs parcimonieux. - Marta Avalos; Yves Grandvalet; Christophe Ambroise (Rev. d'Intelligence Artif., 2005)

Driving Hierarchy Construction via Supervised Learning: Application to Osteo-Articular Medical Images Database. - Karim Yousfi; Christophe Ambroise; Jean Pierre Cocquerez; Jonathan Chevelu (ICIP, 2006)

Supervised Learning for Guiding Hierarchy Construction: Application to Osteo-Articular Medical Images Database. - Karim Yousfi; Christophe Ambroise; Jean Pierre Cocquerez; Jonathan Chevelu (ICPR (1), 2006)

A classification EM algorithm for binned data. - Allou Samé; Christophe Ambroise; Gérard Govaert (Comput. Stat. Data Anal., 2006)

Feature selection in robust clustering based on Laplace mixture. - Aurélien Cord; Christophe Ambroise; Jean Pierre Cocquerez (Pattern Recognit. Lett., 2006)

Parsimonious additive models. - Marta Avalos; Yves Grandvalet; Christophe Ambroise (Comput. Stat. Data Anal., 2007)

An online classification EM algorithm based on the mixture model. - Allou Samé; Christophe Ambroise; Gérard Govaert (Stat. Comput., 2007)

Bayesian Methods for Graph Clustering. - Pierre Latouche; Etienne Birmelé; Christophe Ambroise (GfKl, 2008)

Fast online graph clustering via Erdös-Rényi mixture. - Hugo Zanghi; Christophe Ambroise; Vincent Miele (Pattern Recognit., 2008)

SIMoNe: Statistical Inference for MOdular NEtworks. - Julien Chiquet; Alexander Smith 003; Gilles Grasseau; Catherine Matias; Christophe Ambroise (Bioinform., 2009)

Strategies for Online Inference of Model-Based Clustering in large Networks - Hugo Zanghi; Franck Picard; Vincent Miele; Christophe Ambroise (CoRR, 2009)

Clustering based on random graph model embedding vertex features. - Hugo Zanghi; Stevenn Volant; Christophe Ambroise (Pattern Recognit. Lett., 2010)

Inferring multiple graphical structures. - Julien Chiquet; Yves Grandvalet; Christophe Ambroise (Stat. Comput., 2011)

Overlapping Clustering Methods for Networks. - Pierre Latouche; Etienne Birmelé; Christophe Ambroise (Handbook of Mixed Membership Models and Their Applications, 2014)

Significance testing for variable selection in high-dimension. - Jean-Michel Bécu; Christophe Ambroise; Yves Grandvalet; Cyril Dalmasso (CIBCB, 2015)

Performance of a blockwise approach in variable selection using linkage disequilibrium information. - Alia Dehman; Christophe Ambroise; Pierre Neuvial (BMC Bioinform., 2015)

Eigen-Epistasis for detecting gene-gene interactions. - Virginie Stanislas; Cyril Dalmasso; Christophe Ambroise (BMC Bioinform., 2017)

Beyond support in two-stage variable selection. - Jean-Michel Bécu; Yves Grandvalet; Christophe Ambroise; Cyril Dalmasso (Stat. Comput., 2017)

Learning the optimal scale for GWAS through hierarchical SNP aggregation. - Florent Guinot; Marie Szafranski; Christophe Ambroise; Franck Samson (BMC Bioinform., 2018)

Adjacency-constrained hierarchical clustering of a band similarity matrix with application to genomics. - Christophe Ambroise; Alia Dehman; Pierre Neuvial; Guillem Rigaill; Nathalie Villa-Vialaneix (Algorithms Mol. Biol., 2019)

Fast computation of genome-metagenome interaction effects. - Florent Guinot; Marie Szafranski; Julien Chiquet; Anouk Zancarini; Christine Le Signor; Christophe Mougel; Christophe Ambroise (Algorithms Mol. Biol., 2020)

PPanGGOLiN: Depicting microbial diversity via a partitioned pangenome graph. - Guillaume Gautreau; Adelme Bazin; Mathieu Gachet; Rémi Planel; Laura Burlot; Mathieu Dubois; Amandine Perrin; Claudine Médigue; Alexandra Calteau; Stéphane Cruveiller; Catherine Matias; Christophe Ambroise; et al. (PLoS Comput. Biol., 2020)

Correction: PPanGGOLiN: Depicting microbial diversity via a partitioned pangenome graph. - Guillaume Gautreau; Adelme Bazin; Mathieu Gachet; Rémi Planel; Laura Burlot; Mathieu Dubois; Amandine Perrin; Claudine Médigue; Alexandra Calteau; Stéphane Cruveiller; Catherine Matias; Christophe Ambroise; et al. (PLoS Comput. Biol., 2021)

Inference of Multiscale Gaussian Graphical Model. - Do Edmond Sanou; Christophe Ambroise; Geneviève Robin (CoRR, 2022)

Hierarchical correction of p-values via an ultrametric tree running Ornstein-Uhlenbeck process. - Antoine Bichat; Christophe Ambroise; Mahendra Mariadassou (Comput. Stat., 2022)

Mixture of stochastic block models for multiview clustering. - Kylliann De Santiago; Marie Szafranski; Christophe Ambroise (ESANN, 2023)

Mixture of multilayer stochastic block models for multiview clustering. - Kylliann De Santiago; Marie Szafranski; Christophe Ambroise (CoRR, 2024)