A supervised clustering approach for extracting predictive information from brain activation images. - Vincent Michel; Evelyn Eger; Christine Keribin; Jean-Baptiste Poline; Bertrand Thirion (CVPR Workshops, 2010)

Multi-Class Sparse Bayesian Regression for Neuroimaging Data Analysis. - Vincent Michel; Evelyn Eger; Christine Keribin; Bertrand Thirion (MLMI, 2010)

Multiclass Sparse Bayesian Regression for fMRI-Based Prediction. - Vincent Michel; Evelyn Eger; Christine Keribin; Bertrand Thirion (Int. J. Biomed. Imaging, 2011)

A supervised clustering approach for fMRI-based inference of brain states. - Vincent Michel; Alexandre Gramfort; Gaël Varoquaux; Evelyn Eger; Christine Keribin; Bertrand Thirion (Pattern Recognit., 2012)

Estimation and selection for the latent block model on categorical data. - Christine Keribin; Vincent Brault; Gilles Celeux; Gérard Govaert (Stat. Comput., 2015)

Risk Bounds for Positive-Unlabeled Learning Under the Selected At Random Assumption. - Olivier Coudray; Christine Keribin; Pascal Massart; Patrick Pamphile (J. Mach. Learn. Res., 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)

SubSearch: Robust Estimation and Outlier Detection for Stochastic Block Models via Subgraph Search. - Leonardo Martins Bianco; Christine Keribin; Zacharie Naulet (AISTATS, 2025)