Publications

Publications 2020- :

• MMD Aggregated Two-Sample Test,   A Schrab, I Kim, M Albert, B Laurent, B Guedj, A Gretton,  2023, Journal of Machine Learning Research, JMLR, 24(194):1−81.
• Counterfactual Explanation for Multivariate Times Series Using A Contrastive Variational Autoencoder W Todo, M Selmani, B Laurent, JM Loubes
  ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing.

• Aggregated test of independence based on HSIC measures, M. Albert, B.Laurent, A. Marrel, A.Meynaoui,  2022, Annals of Statistics Vol. 50, No. 2, 858-879.
  

• Minimax optimal goodness-of-fit testing for densities and multinomials under a local differential privacy constraint , J. Lam, B.Laurent, J.M. Loubes,  2022, Bernoulli,  Vol. 28, No. 1, 579-600.
  

• Multiple testing for outlier detection in functional data, C. Barreyre, B.Laurent, J.M. Loubes, B. Cabon, L. Boussouf, 2020,   IEEE Transactions on Big Data.

Publications 2010-2019 :

• New statistical methodology for second level global sensitivity analysis, A.Meynaoui, A. Marrel, B.Laurent, 2019, Pré-publication hal-02019412v1  
• Wikistat 2.0: Ressources pédagogiques pour l’Intelligence Artificielle, P. Besse, B. Guillouet, B. Laurent, 2018,  Statistique et Enseignement  Vol.9 (1),  hal-01883120v2.
• Multidimensional two-components Gaussian mixtures detection, B. Laurent., C. Marteau, C. Maugis-Rabusseau, 2018,  Ann. Inst. Henri Poincaré Probab. Stat. 54, no. 2, 842–865.
• Non asymptotic detection of two component mixtures with unknown means, B. Laurent., C. Marteau, C. Maugis-Rabusseau, 2016,  Bernoulli 22(1), 2016, 242–274.
• De statisticien à Data Scientist, développements pédagogiques à l’INSA de Toulouse, P. Besse, B. Laurent, 2016, SFDS – Statistique et Enseignement, Vol. 7, No 1.
• Signal detection for inverse problems in a multidimensional framework, Y. Ingster, B. Laurent, C. Marteau,  Math. Methods Statist.  23 (2014), no. 4, 279–305.
• Selection of fixed effects in high dimensional linear mixed models using a multicycle ECM algorithm, Rohart F., San Cristobal M. and Laurent B. , 2014 Computational Statistics & Data Analysis. DOI: 10.1016/j.csda.2014.06.022
• The two-sample problem for Poisson processes: adaptive tests with a non-asymptotic wild bootstrap approach, M. Fromont, B. Laurent., P. Reynaud-Bouret, The Annals of Statistics 2013, Vol. 41, No. 3, 1431–1461
•  Estimation of the Sobol indices in a linear functional multidimensional model, J.C. Fort, T. Klein, A. Lagnoux and  B. Laurent, 2013,  Journal of Statistical Planning and Inference 143, No 9, 1590-1605.
• Multilayer perceptron for learning spatio-temporal dynamics-Applications in thermal ingeneering, M. De Lozzo, P. Klotz, B. Laurent, 2013  Ingeneering Applications of Artificial Intelligence, Vol. 26, No. 10.
• Kernels Based Tests with Non-asymptotic Bootstrap Approaches for Two-sample Problems, M. Fromont, B. Laurent., M. Lerasle,  P. Reynaud-Bouret  COLT 2012, JMLR W&CP 23: 23.1 – 23.23.
• Non asymptotic minimax rates of testing in signal detection with heterogeneous variances, B. Laurent, J.M. Loubes, C. Marteau,  Electronic Journal of Statistics 2012, Vol. 6, No. 0, 91-122.
• Adaptive tests of homogeneity for a Poisson process, M. Fromont, B. Laurent., P. Reynaud-Bouret,  Annales de l’Institut Henri Poincaré (B), 2011, Vol. 47, No. 1, 176-213.
• Global sensitivity analysis for models with spatially dependent outputs, A. Marrel, B. Iooss, M. Jullien, B. Laurent, E. Volkova,  Environmetrics, 2011,  vol. 22, 383-397.
• Testing inverse problems : a direct or an indirect problem ?, B. Laurent, J.M. Loubes, C. Marteau,  Journal of Statistical Planning and Inference, 2011,  vol.  141, 1849-1861.

Analyse de données post-génomiques : 

•    Phenotypic prediction based on metabolomic data on the growing pig from three main European breeds, F. Rohart, A. Paris, B. Laurent, C. Canlet, J. Molina, M.J. Mercat, T. Tribout, N. Muller, I. Iannuccelli, N. Villa-Vialaneix, L. Liaubet, D. Milan and M. San Cristobal . Journal of Animal Science, 2012, 90(13):4729-40.
•    Bacterial translational regulations: high diversity between all mRNAs and major role in gene expression, Flora Picard, Hélène Milhem, Pascal Loubière, Béatrice Laurent, Muriel Cocaign-Bousquet and Laurence Girbal, BMC Genomics, 2012, 13 : 528.
• Linear covariance models to examine the determinants of protein levels in Lactococcus lactis, C. Dressaire, B. Laurent, P. Loubière, P. Besse, M. Cocaign-Bousquet. Molecular BioSystems, 2010, 6, 1255-1264.

 Publications 2000-2009- :

•  Calculations of the Sobol indices for the Gaussian process metamodel. A. Marrel, B. Iooss, B. Laurent, O. Roustant. Reliability Engineering and System Safety, 2009, 94:742-75.
•  Adaptive estimation of linear functionals by model selection. B. Laurent, C. Ludena, C. Prieur. Electronic Journal of Statistics, 2008, vol. 2, 993-1020.
• Adaptive goodness-of-fit tests in a density model.   M. Fromont et B. Laurent. The Annals of Statistics, 2006, Vol. 34,  No 2. p.1-45.
• Adaptive estimation of a quadratic functional of a density by model selection.   B. Laurent. ESAIM P & S, 2005, Vol. 9, p. 1-18.
•  Testing convex hypotheses on the mean of a Gaussian vector  Y. Baraud, S. Huet,   B. Laurent. The Annals of Statistics, 2005, Vol. 33,  No 1. p. 214-257.
• Adaptive tests of qualitative hypotheses by model selection. Y. Baraud, S. Huet, B. Laurent.ESAIM P & S, 2003, Vol. 7, p. 147.
• Adaptive tests of linear hypotheses by model selection. Y. Baraud, S. Huet, B. Laurent. The Annals of Statistics, 2003, Vol. 31,  No 1, p. 225-251.
•  A new test of linear hypothesis in regression. Y. Baraud, S. Huet, B. Laurent.« Goodness-of-Fit Tests and  Model Validity », 2001, p. 195-206.
•  Adaptive estimation of a quadratic functional by model selection. B. Laurent et P. Massart. The Annals of Statistics, 2000, Vol. 28,  No 5, p. 1302-1338 .