Invited lectures

Speakers invited by the Scientific Committee of the JdS 2023 :

Natalia BOCHKINA (University of Edinburgh):  "Semiparametric Bernstein-von Mises theorem for a linear model with one-sided error"

Fabienne COMTE (Université Paris Cité): "Estimation non paramétrique et à support non compact en régression : l'exemple des modèles de survie"

Susanne DITLEVSEN (University of Copenhagen): "Prediction of tipping points in the times"

Jelle GOEMAN (Universiteit Leiden): "All-resolutions inference: adaptively choosing the scale of your analysis"

Camelia GOGA (Université de Franche-Comté) : "Estimation de type "model-assisted" dans un cadre de grande dimension pour des données d'enquêtes"

Lester MACKEY (Stanford University): "Advances in distribution compression"

Philippe NAVEAU (Laboratoire des Sciences du Climat et de l’Environnement (LSCE), CNRS): "Développements d'outils statistiques pour l'attribution d'événements extrêmes climatiques"

Laura SANGALLI (Politecnico di Milano): "Physics-informed spatial and functional data analysis over non-Euclidean domains"

Nicolas VERZELEN (Université de Montpellier): "Estimation de permutation pour des modèles de crowdsourcing non-paramétriques"

Thomas WOLF (Huggingface) : "Création de modèles de langue de grande taille en open-source : défis et opportunités" CANCELLED

In addition, during this 54^th edition of the Journées de Statistique, the SFdS will award the Marie-Jeanne Laurent-Duhamel Prize, which is intended to highlight the quality of the thesis work of a young French-speaking statistician. In 2023, the prize will be awarded for a remarkable contribution to fundamental research.

During the JdS 2023, the Doctor Norbert Marx Prize will also be given. This prize is awarded every two years for work in applied statistical methodology in the fields of epidemiology, public health or health economics.

Finally, as every year, the Lucien Le Cam Conference, created in memory of this great statistician, will be held during the JdS. This plenary conference aims to promote new statistical methods or to deepen the knowledge of some specific theories.