Research

Since September 2020, I am a PhD student in statistics, under the supervision of Anne-Laure Fougères and Clément Dombry. My research interests are the assessment of the quality of a random forecast and recently the study of the Maximum Mean Discrepancy (MMD) in the RKHS theory.


Publications and preprints:


  • Characterization of translation invariant MMD on Rd and connections with Wasserstein distances, with C. Dombry. Hal, 2022, in Journal of Machine Learning Research.

  • Stone's theorem for distributional regression in Wasserstein distance, with C. Dombry and R. Pic. Hal, 2023, in Journal of Nonparametric Statistics.

  • Testing ideal calibration for sequential predictions, with C. Dombry and A.-L. Fougères. On request, 2023.

  • Modeling and scoring dynamic probabilistic forecasts, with C. Dombry and A.-L. Fougères. Hal, 2023.

  • Manuscrit de thèse :
    Voici le manuscrit de ma thèse effectuée entre 2020 et 2023.