Model-agnostic out-of-distribution detection using combined statistical tests. - Federico Bergamin; Pierre-Alexandre Mattei; Jakob Drachmann Havtorn; Hugo Sénétaire; Hugo Schmutz; Lars Maaløe; Søren Hauberg; Jes Frellsen (AISTATS, 2022)

Don't fear the unlabelled: safe deep semi-supervised learning via simple debiasing. - Hugo Schmutz; Olivier Humbert; Pierre-Alexandre Mattei (CoRR, 2022)

Don't fear the unlabelled: safe semi-supervised learning via debiasing. - Hugo Schmutz; Olivier Humbert; Pierre-Alexandre Mattei (ICLR, 2023)

Are labels informative in semi-supervised learning? Estimating and leveraging the missing-data mechanism. - Aude Sportisse; Hugo Schmutz; Olivier Humbert; Charles Bouveyron; Pierre-Alexandre Mattei (ICML, 2023)

Semi-supervised learning, PET/CT segmentation and prediction of the tumoral response to immunotherapy. (Apprentissage semi-supervisé, segmentation d'images TEP/TDM et prédiction de la réponse tumorale à l'immunothérapie). - Hugo Schmutz (2023)