Imputation and low-rank estimation with Missing Non At Random data. - Aude Sportisse; Claire Boyer; Julie Josse (CoRR, 2018)

Debiasing Averaged Stochastic Gradient Descent to handle missing values. - Aude Sportisse; Claire Boyer; Aymeric Dieuleveut; Julie Josse (NeurIPS, 2020)

Estimation and Imputation in Probabilistic Principal Component Analysis with Missing Not At Random Data. - Aude Sportisse; Claire Boyer; Julie Josse (NeurIPS, 2020)

Imputation and low-rank estimation with Missing Not At Random data. - Aude Sportisse; Claire Boyer; Julie Josse (Stat. Comput., 2020)

R-miss-tastic: a unified platform for missing values methods and workflows. - Imke Mayer; Aude Sportisse; Julie Josse; Nicholas J. Tierney; Nathalie Vialaneix (R J., 2022)

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)

Fed-MIWAE: Federated Imputation of Incomplete Data via Deep Generative Models. - Irene Balelli; Aude Sportisse; Francesco Cremonesi; Pierre-Alexandre Mattei; Marco Lorenzi (CoRR, 2023)

Model-based clustering with missing not at random data. - Aude Sportisse; Matthieu Marbac; Fabien Laporte; Gilles Celeux; Claire Boyer; Julie Josse; Christophe Biernacki (Stat. Comput., 2024)