Publications

Working papers

Fed-MIWAE: Federated Imputation of Incomplete Data via Deep Generative Models
Irene Balelli, Aude Sportisse, Francesco Cremonesi, Pierre-Alexandre Mattei, Marco Lorenzi
paper code

Model-based Clustering with Missing Not At Random Data
Aude Sportisse, Christophe Biernacki, Claire Boyer, Julie Josse, Matthieu Marbac, Gilles Celeux, Fabien Laporte
paper accompagnying note (new) code slides

Publications

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 (oral)
paper code poster slides video

R-miss-tastic: a unified platform for missing values methods and workflows
Imke Mayer, Aude Sportisse, Julie Josse, Nicholas Tiernay, Nathalie Vialaneix
R journal, 2022
paper platform code platform

Robust Lasso-Zero for sparse corruption and model selection with missing covariates
Pascaline Descloux, Claire Boyer, Julie Josse, Aude Sportisse, Sylvain Sardy
Scandinavian Journal of Statistics, 2022
paper slides video

Debiasing Stochastic Gradient Descent to handle missing values
Aude Sportisse, Claire Boyer, Aymeric Dieuleveut, Julie Josse
NeurIPS 2020
paper code poster slides

Estimation and Imputation in Probabilistic Principal Component Analysis with Missing Not At Random Data
Aude Sportisse, Claire Boyer, Julie Josse
NeurIPS 2020
paper code poster slides

Imputation and low-rank estimation with Missing Not At Random data
Aude Sportisse, Claire Boyer, Julie Josse
Statistics & Computing, Springer, 2019-2020
paper code slides