Pierre-Alexandre Mattei

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 30

Top Topics

Incomplete Data

Generative Model

Statistical Tests

Supervised Learning

Top Venues

Publications

Louis Ohl, Pierre-Alexandre Mattei, Charles Bouveyron, Mickaël Leclercq, Arnaud Droit, Frédéric Precioso
Sparse and geometry-aware generalisation of the mutual information for joint discriminative clustering and feature selection. Stat. Comput. 34 (5) (2024)
Louis Ohl, Pierre-Alexandre Mattei, Mickaël Leclercq, Arnaud Droit, Frédéric Precioso
Kernel KMeans clustering splits for end-to-end unsupervised decision trees. CoRR (2024)
Hugo Henri Joseph Sénétaire, Damien Garreau, Jes Frellsen, Pierre-Alexandre Mattei
Explainability as statistical inference. ICML (2023)
Hugo Schmutz, Olivier Humbert, Pierre-Alexandre Mattei
Don't fear the unlabelled: safe semi-supervised learning via debiasing. ICLR (2023)
Irene Balelli, Aude Sportisse, Francesco Cremonesi, Pierre-Alexandre Mattei, Marco Lorenzi
Fed-MIWAE: Federated Imputation of Incomplete Data via Deep Generative Models. CoRR (2023)
Louis Ohl, Pierre-Alexandre Mattei, Charles Bouveyron, Mickaël Leclercq, Arnaud Droit, Frédéric Precioso
Sparse GEMINI for Joint Discriminative Clustering and Feature Selection. CoRR (2023)
Pierre-Alexandre Mattei, Damien Garreau
Are ensembles getting better all the time? CoRR (2023)
Aude Sportisse, Hugo Schmutz, Olivier Humbert, Charles Bouveyron, Pierre-Alexandre Mattei
Are labels informative in semi-supervised learning? Estimating and leveraging the missing-data mechanism. ICML (2023)
Louis Ohl, Pierre-Alexandre Mattei, Charles Bouveyron, Warith Harchaoui, Mickaël Leclercq, Arnaud Droit, Frédéric Precioso
Generalised Mutual Information: a Framework for Discriminative Clustering. CoRR (2023)
Melissa Sanabria, Frédéric Precioso, Pierre-Alexandre Mattei, Thomas Menguy
A Multi-stage deep architecture for summary generation of soccer videos. CoRR (2022)
Rima Khouja, Pierre-Alexandre Mattei, Bernard Mourrain
Tensor decomposition for learning Gaussian mixtures from moments. J. Symb. Comput. 113 (2022)
Michael Fop, Pierre-Alexandre Mattei, Charles Bouveyron, Thomas Brendan Murphy
Unobserved classes and extra variables in high-dimensional discriminant analysis. Adv. Data Anal. Classif. 16 (1) (2022)
Louis Ohl, Pierre-Alexandre Mattei, Charles Bouveyron, Warith Harchaoui, Mickaël Leclercq, Arnaud Droit, Frédéric Precioso
Generalised Mutual Information for Discriminative Clustering. CoRR (2022)
Louis Ohl, Pierre-Alexandre Mattei, Charles Bouveyron, Warith Harchaoui, Mickaël Leclercq, Arnaud Droit, Frédéric Precioso
Generalised Mutual Information for Discriminative Clustering. NeurIPS (2022)
Pierre-Alexandre Mattei, Jes Frellsen
Uphill Roads to Variational Tightness: Monotonicity and Monte Carlo Objectives. CoRR (2022)
Niels Bruun Ipsen, Pierre-Alexandre Mattei, Jes Frellsen
How to deal with missing data in supervised deep learning? ICLR (2022)
Federico Bergamin, Pierre-Alexandre Mattei, Jakob D. Havtorn, Hugo Senetaire, Hugo Schmutz, Lars Maaløe, Søren Hauberg, Jes Frellsen
Model-agnostic out-of-distribution detection using combined statistical tests. CoRR (2022)
Hugo Henri Joseph Sénétaire, Damien Garreau, Jes Frellsen, Pierre-Alexandre Mattei
Explainability as statistical inference. CoRR (2022)
Federico Bergamin, Pierre-Alexandre Mattei, Jakob Drachmann Havtorn, Hugo Sénétaire, Hugo Schmutz, Lars Maaløe, Søren Hauberg, Jes Frellsen
Model-agnostic out-of-distribution detection using combined statistical tests. AISTATS (2022)
Hugo Schmutz, Olivier Humbert, Pierre-Alexandre Mattei
Don't fear the unlabelled: safe deep semi-supervised learning via simple debiasing. CoRR (2022)
Niels Bruun Ipsen, Pierre-Alexandre Mattei, Jes Frellsen
not-MIWAE: Deep Generative Modelling with Missing not at Random Data. ICLR (2021)
Niels Bruun Ipsen, Pierre-Alexandre Mattei, Jes Frellsen
not-MIWAE: Deep Generative Modelling with Missing not at Random Data. CoRR (2020)
Pierre-Alexandre Mattei, Jes Frellsen
MIWAE: Deep Generative Modelling and Imputation of Incomplete Data Sets. ICML (2019)
Samuel Wiqvist, Pierre-Alexandre Mattei, Umberto Picchini, Jes Frellsen
Partially Exchangeable Networks and Architectures for Learning Summary Statistics in Approximate Bayesian Computation. CoRR (2019)
Samuel Wiqvist, Pierre-Alexandre Mattei, Umberto Picchini, Jes Frellsen
Partially Exchangeable Networks and Architectures for Learning Summary Statistics in Approximate Bayesian Computation. ICML (2019)
Pierre-Alexandre Mattei, Jes Frellsen
Leveraging the Exact Likelihood of Deep Latent Variable Models. NeurIPS (2018)
Pierre-Alexandre Mattei, Jes Frellsen
Leveraging the Exact Likelihood of Deep Latent Variable Models. CoRR (2018)
Pierre-Alexandre Mattei, Jes Frellsen
missIWAE: Deep Generative Modelling and Imputation of Incomplete Data. CoRR (2018)
Pierre Latouche, Pierre-Alexandre Mattei, Charles Bouveyron, Julien Chiquet
Combining a relaxed EM algorithm with Occam's razor for Bayesian variable selection in high-dimensional regression. J. Multivar. Anal. 146 (2016)
Pierre-Alexandre Mattei, Charles Bouveyron, Pierre Latouche
Globally Sparse Probabilistic PCA. AISTATS (2016)