Christophe Ambroise
Christophe Ambroise
Professor of Statistics, Université d'Evry Val d'Essonne
Verified email at - Homepage
Cited by
Cited by
Selection bias in gene extraction on the basis of microarray gene-expression data
C Ambroise, GJ McLachlan
Proceedings of the national academy of sciences 99 (10), 6562-6566, 2002
Analyzing microarray gene expression data
GJ McLachlan, KA Do, C Ambroise
John Wiley & Sons, 2005
Overlapping stochastic block models with application to the french political blogosphere
P Latouche, E Birmelé, C Ambroise
Variational Bayesian inference and complexity control for stochastic block models
P Latouche, E Birmele, C Ambroise
Statistical Modelling 12 (1), 93-115, 2012
Clustering of spatial data by the EM algorithm
C Ambroise, M Dang, G Govaert
geoENV I—Geostatistics for Environmental Applications: Proceedings of the …, 1997
Hierarchical clustering of self-organizing maps for cloud classification
C Ambroise, G Sèze, F Badran, S Thiria
Neurocomputing 30 (1-4), 47-52, 2000
PPanGGOLiN: depicting microbial diversity via a partitioned pangenome graph
G Gautreau, A Bazin, M Gachet, R Planel, L Burlot, M Dubois, A Perrin, ...
PLoS computational biology 16 (3), e1007732, 2020
Fast online graph clustering via Erdős–Rényi mixture
H Zanghi, C Ambroise, V Miele
Pattern recognition 41 (12), 3592-3599, 2008
Semi-supervised marginboost
F d'Alché-Buc, Y Grandvalet, C Ambroise
Advances in neural information processing systems 14, 2001
Convergence of an EM-type algorithm for spatial clustering
C Ambroise, G Govaert
Pattern recognition letters 19 (10), 919-927, 1998
Inferring multiple graphical structures
J Chiquet, Y Grandvalet, C Ambroise
Statistics and Computing 21, 537-553, 2011
Clustering based on random graph model embedding vertex features
H Zanghi, S Volant, C Ambroise
Pattern Recognition Letters 31 (9), 830-836, 2010
Accounting for population stratification in practice: a comparison of the main strategies dedicated to genome-wide association studies
M Bouaziz, C Ambroise, M Guedj
PloS one 6 (12), e28845, 2011
Inferring sparse Gaussian graphical models with latent structure
C Ambroise, J Chiquet, C Matias
Weighted-LASSO for structured network inference from time course data
C Charbonnier, J Chiquet, C Ambroise
Statistical applications in genetics and molecular biology 9 (1), 2010
New consistent and asymptotically normal parameter estimates for random‐graph mixture models
C Ambroise, C Matias
Journal of the Royal Statistical Society: Series B (Statistical Methodology), 2011
Feature selection in robust clustering based on Laplace mixture
A Cord, C Ambroise, JP Cocquerez
Pattern Recognition Letters 27 (6), 627-635, 2006
Epigenetics in forest trees: state of the art and potential implications for breeding and management in a context of climate change
MD Sow, I Allona, C Ambroise, D Conde, R Fichot, S Gribkova, V Jorge, ...
Advances in botanical research 88, 387-453, 2018
Simone: Statistical inference for modular networks
J Chiquet, A Smith, G Grasseau, C Matias, C Ambroise
Bioinformatics 25 (3), 417-418, 2009
An online classification EM algorithm based on the mixture model
A Samé, C Ambroise, G Govaert
Statistics and Computing 17, 209-218, 2007
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