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.
