{"id":67,"date":"2020-08-26T18:58:50","date_gmt":"2020-08-26T16:58:50","guid":{"rendered":"https:\/\/wp.imo.universite-paris-saclay.fr\/christine-keribin\/?page_id=67"},"modified":"2024-10-18T16:01:44","modified_gmt":"2024-10-18T14:01:44","slug":"publications","status":"publish","type":"page","link":"https:\/\/wp.imo.universite-paris-saclay.fr\/christine-keribin\/publications\/","title":{"rendered":"Publications"},"content":{"rendered":"\n

HDR<\/a> (2019), M\u00e9moire de th\u00e8se<\/a> (1999)<\/p>\n\n\n\n\n\n\n\n\t\n\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t
Co-auteurs<\/th>Titre<\/th>Source<\/th>\n<\/tr>\n<\/thead>\n
Baietto M., Coulaud R., Keribin C., Stoltz G.<\/td>Improved real-time crowding information through the modeling of passenger movements in trains with communicating coaches<\/td>https:\/\/hal.science\/hal-05163888 2025 pdf<\/a> <\/td>\n<\/tr>\n
Irlinger F., Keribin C., Sarthou A.-S., Laroche B., Helinck S.<\/td>Pink discoloration defects associated with microbial structure and metabolome changes in commercial bloomy cheeses<\/td>International Journal of Food Microbiology (2025): 111363.
\npdf<\/a> <\/td>\n<\/tr>\n
Martins Bianco L., Keribin C., Naulet Z.<\/td>SubSearch: Robust Estimation and Outlier Detection for Stochastic Block Models via Subgraph Search<\/td>Proceedings of the 28th International Conference on Artificial Intelligence and Statistics (AISTATS) 2025, Mai Khao, Thailand; PMLR: Volume 258. article<\/a> appendix<\/a> poster<\/a> <\/td>\n<\/tr>\n
Coudray O., Bristiel P., Dinis M., Keribin C., Pamphile P.<\/td>Construction of Fatigue Criteria Through Positive-Unlabeled Learning<\/td>FFEMS, 2024, 0:1\u201317 pdf<\/a><\/td>\n<\/tr>\n
Biernacki C., Jacques J., Keribin C.<\/td>A Survey on Model-Based Co-Clustering: High Dimension and Estimation Challenges<\/td>Journal of Classification, p.1-50, 2023 pdf<\/a><\/td>\n<\/tr>\n
Coudray, O., Keribin C., Massart, P., Pamphile, P.<\/td>Risk bounds for PU learning under Selected at Random assumption<\/td>JMLR 24, 2023: p 1\u221231
\npdf<\/a><\/td>\n<\/tr>\n
Antonazzo F., Biernacki C., Keribin C.<\/td>Frugal Gaussian clustering of huge imbalanced datasets through a bin-marginal approach<\/td>Statistics and Computing, 2023, vol. 33, no 3, p. 1-22
\n pdf<\/a><\/td>\n<\/tr>\n
Coulaud R., Keribin C., Stoltz G.<\/td>Modeling dwell time in a data-rich railway environment: With operations and passenger flows data<\/td>Transportation Research Part C: Emerging Technologies, 2023, vol. 146, p. 103980<\/td>\n<\/tr>\n
Keribin C.<\/td>Cluster or co-cluster the nodes of oriented graphs?<\/td>Journal de la Soci\u00e9t\u00e9 Fran\u00e7aise de Statistique 162(1), 2021, pdf<\/a><\/td>\n<\/tr>\n
Brault V., Keribin C., Mariadassou M.<\/td>Consistency and Asymptotic Normality of Latent Blocks Model Estimators <\/td>Electron. J. Statist.
\n14(1), 2020, pdf<\/a><\/td>\n<\/tr>\n
Keribin C.<\/td>A note on BIC and the slope heuristics<\/td>Journal de la SFdS
\n160(3), 2019, pdf<\/a><\/td>\n<\/tr>\n
Keribin C., Liu Y. Popova T., Rozenholc Y.<\/td>A mixture model to characterize genomic alterations of tumors<\/td>Journal de la SFdS
\n160(1), 2019, pdf<\/a><\/td>\n<\/tr>\n
Hernandez C., Keribin C., Drobinski P., Turquety S.<\/td>Statistical modelling of wildfire size and intensity: a step toward meteorological forecasting of summer extreme fire risk<\/td>Annales Geophysicae
\n33, 2015, pdf<\/a><\/td>\n<\/tr>\n
Keribin C., Brault V., Celeux G., Govart G.<\/td>Estimation and Selection for the Latent Block Model on Categorical Data<\/td>Statistics and Computing
\n25 (6), 2015, pdf<\/a><\/td>\n<\/tr>\n
Michel V., Gramfort A., Varoquaux G.,Eger E., Keribin C., and Thirion B.<\/td>A supervised clustering approach for fMRI-based inference of brain states<\/td>Pattern Recognition \u2013 Special Issue on Brain Decoding
\n45(6), 2012, pdf<\/a><\/td>\n<\/tr>\n
Michel V., Eger E., Keribin C. and Thirion B.<\/td>Multi-Class Sparse Bayesian Regression for fRMI-based prediction<\/td>International Journal of Biomedical Imaging
\n2011, pdf<\/a><\/td>\n<\/tr>\n
Keribin C.<\/td>M\u00e9thodes bay\u00e9siennes variationnelles : concepts et applications en neuroimagerie<\/td>Journal de la Soci\u00e9t\u00e9 Fran\u00e7aise de Statistique
\n151(2), 2010, pdf<\/a><\/td>\n<\/tr>\n
Keribin C., Haughton D.<\/td>Asymptotic probabilities of over-estimating and under-estimating the order of a model in general regular families<\/td>Communications in Statistics, Theory and Methods
\n32-7, 2003<\/td>\n<\/tr>\n
Gassiat E. , Keribin C.<\/td>The Likelihood Ratio Test for the number of components of a mixture with Markov regime<\/td>ESAIM PS Vol 4, 2000<\/td>\n<\/tr>\n
Keribin C.<\/td>Consistent Estimation of the Order of Mixture Models<\/td>Sankhya Series A
\nvolume 62, Part. 1, 2000, pdf<\/a><\/td>\n<\/tr>\n
Keribin C.<\/td>Estimation consistante de l\u2019ordre de mod\u00e8les de m\u00e9lange<\/td>CRAS
\nS\u00e9rie I, 326(2), 1998<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n\n\n

Actes de conf\u00e9rences<\/h2>\n\n\n\n