Mattei, Pierre-Alexandre

13 publications

JMLR 2025 Are Ensembles Getting Better All the Time? Pierre-Alexandre Mattei, Damien Garreau

ICML 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

ICLR 2023 Don’t Fear the Unlabelled: Safe Semi-Supervised Learning via Debiasing Hugo Schmutz, Olivier Humbert, Pierre-Alexandre Mattei

ICML 2023 Explainability as Statistical Inference Hugo Henri Joseph Senetaire, Damien Garreau, Jes Frellsen, Pierre-Alexandre Mattei

AISTATS 2022 Model-Agnostic Out-of-Distribution Detection Using Combined Statistical Tests Federico Bergamin, Pierre-Alexandre Mattei, Jakob Drachmann Havtorn, Hugo Sénétaire, Hugo Schmutz, Lars Maaløe, Soren Hauberg, Jes Frellsen

NeurIPS 2022 Generalised Mutual Information for Discriminative Clustering Louis Ohl, Pierre-Alexandre Mattei, Charles Bouveyron, Warith Harchaoui, Mickaël Leclercq, Arnaud Droit, Frederic Precioso

ICLR 2022 How to Deal with Missing Data in Supervised Deep Learning? Niels Bruun Ipsen, Pierre-Alexandre Mattei, Jes Frellsen

ICLR 2021 Not-MIWAE: Deep Generative Modelling with Missing Not at Random Data Niels Bruun Ipsen, Pierre-Alexandre Mattei, Jes Frellsen

ICMLW 2020 How to Deal with Missing Data in Supervised Deep Learning? Niels Bruun Ipsen, Pierre-Alexandre Mattei, Jes Frellsen

ICML 2019 MIWAE: Deep Generative Modelling and Imputation of Incomplete Data Sets Pierre-Alexandre Mattei, Jes Frellsen

ICML 2019 Partially Exchangeable Networks and Architectures for Learning Summary Statistics in Approximate Bayesian Computation Samuel Wiqvist, Pierre-Alexandre Mattei, Umberto Picchini, Jes Frellsen

NeurIPS 2018 Leveraging the Exact Likelihood of Deep Latent Variable Models Pierre-Alexandre Mattei, Jes Frellsen

AISTATS 2016 Globally Sparse Probabilistic PCA Pierre-Alexandre Mattei, Charles Bouveyron, Pierre Latouche