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Laure Sansonnet

Maître de conférences en statistique

UMR MIA Paris-Saclay (équipe SOLsTIS)

Université Paris-Saclay, AgroParisTech, INRAE
Campus Agro Paris-Saclay
22 place de l'Agronomie
91120 Palaiseau

Bureau : E4.224
E-mail : laure.sansonnet -- @ -- agroparistech.fr
Tél. : +33 (0) 1 89 10 09 66

Publications

Preprints

  • C. Denis, C. Dion-Blanc, R. Lacoste, L. Sansonnet and Y. Bas Bats Monitoring: A Classification Procedure of Bats Behaviors based on Hawkes Processes Submitted [hal-04345822], 2023.
  • M. Gomtsyan, C. Lévy-Leduc, S. Ouadah, L. Sansonnet, C. Bailly and L. Rajjou Variable selection in sparse multivariate GLARMA models: Application to germination control by environment Submitted [hal-03905876], 2023.

Accepted/Published papers

  1. M. Gomtsyan, C. Lévy-Leduc, S. Ouadah and L. Sansonnet Sign consistent estimation in a sparse Poisson model Statistics & Probability Letters 209 [DOI: 10.1016/j.spl.2024.110107], 2024.
  2. M. Naveau, G. Kon Kam King, R. Rincent, L. Sansonnet and M. Delattre Bayesian high-dimensional covariate selection in non-linear mixed-effects models using the SAEM algorithm Statistics and Computing 34(53) [DOI: 10.1007/s11222-023-10367-4], 2024.
  3. C. Denis, C. Dion-Blanc and L. Sansonnet Multiclass Classification for Hawkes Processes Proceedings of the 38th Conference on Uncertainty in Artificial Intelligence (UAI 2022), PMLR 180: 539-547 [https://proceedings.mlr.press/v180/denis22a.html], 2022.
  4. M. Gomtsyan, C. Lévy-Leduc, S. Ouadah, L. Sansonnet and T. Blein Variable selection in sparse GLARMA models Statistics 56(4): 755-784 [DOI: 10.1080/02331888.2022.2090943], 2022.
  5. C. Denis, E. Lebarbier, C. Lévy-Leduc, O. Martin and L. Sansonnet A novel regularized approach for functional data clustering: An application to milking kinetics in dairy goats Journal of the Royal Statistical Society: Series C (Applied Statistics) 69(3): 623-640 [DOI: 10.1111/rssc.12404], 2020.
  6. M. Grandclaudon, M. Perrot-Dockès, C. Trichot, L. Karpf, O. Abouzid, C. Chauvin, P. Sirven, W. Abou-Jaoudé, F. Berger, P. Hupé, D. Thieffry, L. Sansonnet, J. Chiquet, C. Lévy-Leduc and V. Soumelis A quantitative multivariate model of human dendritic cell-T helper cell communication Cell 179(2): 432-447 [DOI: 10.1016/j.cell.2019.09.012], 2019.
  7. X. J. Hunt, P. Reynaud-Bouret, V. Rivoirard, L. Sansonnet and R. Willett A data-dependent weighted LASSO under Poisson noise IEEE Transactions on Information Theory 65(3): 1589-1613 [DOI: 10.1109/TIT.2018.2869578], 2019.
  8. M. Perrot-Dockès, C. Lévy-Leduc, J. Chiquet, L. Sansonnet, M. Brégère, M.-P. Étienne, S. Robin and G. Genta-Jouve A variable selection approach in the multivariate linear model: an application to LC-MS metabolomics data Statistical Applications in Genetics and Molecular Biology 17(5) [DOI: 10.1515/sagmb-2017-0077], 2018.
  9. M. Perrot-Dockès, C. Lévy-Leduc, L. Sansonnet and J. Chiquet Variable selection in multivariate linear models with high-dimensional covariance matrix estimation Journal of Multivariate Analysis 166: 78-97 [DOI: 10.1016/j.jmva.2018.02.006], 2018.
  10. V. Brault, S. Ouadah, L. Sansonnet and C. Lévy-Leduc Nonparametric multiple change-point estimation for analyzing large Hi-C data matrices Journal of Multivariate Analysis 165: 143-165 [DOI: 10.1016/j.jmva.2017.12.005], 2018.
  11. F. Roueff, R. von Sachs and L. Sansonnet Locally stationary Hawkes processes Stochastic Processes and their Applications 126(6): 1710-1743 [DOI: 10.1016/j.spa.2015.12.003], 2016.
  12. L. Sansonnet and C. Tuleau-Malot A model of Poissonian interactions and detection of dependence Statistics and Computing 25: 449-470 [DOI: 10.1007/s11222-013-9443-z], 2015.
  13. L. Sansonnet Wavelet thresholding estimation in a Poissonian interactions model with application to genomic data Scandinavian Journal of Statistics 41(1): 200-226 [DOI: 10.1111/sjos.12009], 2014.

Publications