Laboratoire de Mathématiques Appliquées de Compiègne

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LMAC

Membres

Annuaire des membres du Laboratoire de Mathématiques Appliquées de Compiègne(LMAC)

ghislaine.gayraud@utc.fr

Ghislaine Gayraud

Statut : Professeure des Universités

Bureau : GI 124

Research interests

  • Bayesian nonparametric
  • Minimax hypothesis testing
  • High dimensional problems
  • Modelling and statistical inference for dependent data
  • Applications to gene regulatory networks

Projets

  • AAP équipes projets ISCD : ``Num4Lyme’’ (2023 - 2026) ; PI : I. Maffuci, GEC-UTC
    Co-responsabilité du développement de modèles stochastiques bio-inspirés par des molécules pour l’aide au diagnostic de la maladie de Lyme
  • AAP UTC-AMI Covid 19 ``Coveille’’ (2020-2021) ;
    PI : M. Davila-Felipe, LMAC-UTC

    Veille de la propagation du virus au travers de la modélisation de la dynamique de l’épidémie du Covid-19 à différents niveaux de granularité

Travaux récents

  • Bayolo Soler, G., Dávila Felipe, M., Gayraud, G. (2023). Test allocation based on risk of infection from first and second-order contact tracing. HAL-04267859
  • Votsi, I., Gayraud, G., Barbu, V. S., Limnios, N. (2021). Hypotheses testing and posterior concentration rates for
    semi-Markov processes, Stat. Inference Stoch. Process., 24, 707—732
  • Wiecek, W., Bois F., Gayraud, G. (2019) Structure learning of Bayesian networks involving cyclic structures. Hal-02130362
  • Zgheib, E., Gao, W., Limonciel, A., Aladjov, H., Yang, H., Tebby, C., Gayraud, G., Jennings, P., Sachana, M., Beltman, J.B., Bois, F.Y. (2019). Application of three approaches for quantitative AOP development to renal toxicity. Computational Toxicology, No. 11, 1—13
  • Datta, S., Gayraud, G., Leclerc, E., Bois, F.Y. (2017) Graph_sampler : a simple tool for fully Bayesian analyses of DAG-models, Computational Statistics, 32, No. 2, 691—716.
  • Butucea, C., Gayraud, G. (2016), Sharp detection of smooth signals in a high-dimensional sparse matrix with indirect observations, Ann. Inst. H. Poincaré Probab. Statist. "Probabilités & Statistiques", 52, No. 4, 1564—1591
  • Bernardi, M., Gayraud, G., Petrella, L. (2015), Bayesian tail risk interdependence using quantile regression, Bayesian Analysis, 10, 553—603
  • Bois, F., Gayraud, G. (2015), Probabilistic generation of random networks taking into account information on motifs occurrence, Journal of Computational Biology, 22, 25—36
  • Arbel, J., Gayraud, G., Rousseau, J. (2013), Bayesian optimal adaptive estimation using a sieve prior, Scandinavian Journal of Statistics, 40, 549—570
  • Gayraud, G., Ingster, Yu. (2012), Detection of sparse additive functions, Electronic Journal of Statistics, 6, 1409-1448
  • Gayraud, G., Tribouley, K. (2011), A goodness-of-fit test for copula densities, Test, 20, 549—573
  • Gayraud, G. (2008), To perform the convergence rate of the Bayesian level set estimate ?, Proceedings of Multimodality and Related Topics, Publication de l’Université Paris X-Nanterre.
  • Gayraud, G., Rousseau, J. (2007), Consistency results on nonparametric Bayesian estimation of level sets using spatial priors, Test, 16, 90—108
  • Gayraud, G., Rousseau, J. (2005), Rates of Convergence for a Bayesian Level set estimation, Scandinavian Journal of Statistics, 32, 639—660
  • Gayraud, G., Pouet, Ch. (2005), Adaptive minimax testing in the discrete regression scheme, Probability Theory and Related Fields, 4, 531—558
  • Gayraud, G. (2002), Minimax estimation of a discontinuity for the density, Journal of Nonparametric Statistics, 14, 59—66
  • Gayraud, G., Tsybakov, A.B. (2002), Testing hypotheses about contours in images, Journal of Nonparametric Statistics, 14, 67—85
  • Gayraud, G. (2001), Minimax hypotheses testing about the density support, Bernoulli, 7, 507—526
  • Gayraud, G., Pouet, Ch. (2001), Minimax testing composite null hypotheses in the discrete regression scheme, Mathematical Methods of Statistics, 10, 375—394
  • Gayraud, G., Tribouley, K. (1999), Adaptive Estimation and Confidence Interval for a Quadratic Functional by Wavelet, Statistic and probability letters, 44, 109—122
  • Gayraud, G. (1997), Estimation of functionals of density support, Mathematical Methods of Statistics, 6, 26—47
 

Adresse

LMAC EA 2222
Université de Technologie de Compiègne
CS 60319 - 57 avenue de Landshut
COMPIEGNE CEDEX , 60203 FRANCE
  • Tél. 03 44 23 46 43
  • Fax. 03 44 23 44 77

Université de Technologie de Compiègne Département Génie Informatique Centre de Recherches de Royallieu

 

Contacts

    Directeur
  • Salim Bouzebda
  • salim.bouzebda[at]utc.fr
  • Tél. 03 44 23 44 69
    Directeur adjoint
  • Ahmad El Hajj
  • ahmad.el-hajj[at]utc.fr
  • Tél. 03 44 23 49 03
    Secrétariat
  • Maryline Schaefflen
  • maryline.schaefflen[at]utc.fr
  • Tél. 03 44 23 46 43