Pierre-Alexandre Mattei

According to our database, Pierre-Alexandre Mattei authored at least 24 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Sparse and geometry-aware generalisation of the mutual information for joint discriminative clustering and feature selection.

Louis Ohl, Pierre-Alexandre Mattei, Charles Bouveyron, Mickaël Leclercq, Arnaud Droit, Frédéric Precioso

Stat. Comput., October, 2024

Kernel KMeans clustering splits for end-to-end unsupervised decision trees.

Louis Ohl, Pierre-Alexandre Mattei, Mickaël Leclercq, Arnaud Droit, Frédéric Precioso

CoRR, 2024

2023

Are ensembles getting better all the time?

Pierre-Alexandre Mattei, Damien Garreau

CoRR, 2023

Generalised Mutual Information: a Framework for Discriminative Clustering.

Louis Ohl, Pierre-Alexandre Mattei, Charles Bouveyron, Warith Harchaoui, Mickaël Leclercq, Arnaud Droit, Frédéric Precioso

CoRR, 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

Sparse GEMINI for Joint Discriminative Clustering and Feature Selection.

Louis Ohl, Pierre-Alexandre Mattei, Charles Bouveyron, Mickaël Leclercq, Arnaud Droit, Frédéric Precioso

CoRR, 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

Proceedings of the International Conference on Machine Learning, 2023

Explainability as statistical inference.

Hugo Henri Joseph Sénétaire, Damien Garreau, Jes Frellsen, Pierre-Alexandre Mattei

Proceedings of the International Conference on Machine Learning, 2023

Don't fear the unlabelled: safe semi-supervised learning via debiasing.

Hugo Schmutz, Olivier Humbert, Pierre-Alexandre Mattei

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Tensor decomposition for learning Gaussian mixtures from moments.

Rima Khouja, Pierre-Alexandre Mattei, Bernard Mourrain

J. Symb. Comput., 2022

A Multi-stage deep architecture for summary generation of soccer videos.

Melissa Sanabria, Frédéric Precioso, Pierre-Alexandre Mattei, Thomas Menguy

CoRR, 2022

Don't fear the unlabelled: safe deep semi-supervised learning via simple debiasing.

Hugo Schmutz, Olivier Humbert, Pierre-Alexandre Mattei

CoRR, 2022

Uphill Roads to Variational Tightness: Monotonicity and Monte Carlo Objectives.

Pierre-Alexandre Mattei, Jes Frellsen

CoRR, 2022

Unobserved classes and extra variables in high-dimensional discriminant analysis.

Michael Fop, Pierre-Alexandre Mattei, Charles Bouveyron, Thomas Brendan Murphy

Adv. Data Anal. Classif., 2022

Generalised Mutual Information for Discriminative Clustering.

Louis Ohl, Pierre-Alexandre Mattei, Charles Bouveyron, Warith Harchaoui, Mickaël Leclercq, Arnaud Droit, Frédéric Precioso

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

How to deal with missing data in supervised deep learning?

Niels Bruun Ipsen, Pierre-Alexandre Mattei, Jes Frellsen

Proceedings of the Tenth International Conference on Learning Representations, 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, Søren Hauberg, Jes Frellsen

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

not-MIWAE: Deep Generative Modelling with Missing not at Random Data.

Niels Bruun Ipsen, Pierre-Alexandre Mattei, Jes Frellsen

Proceedings of the 9th International Conference on Learning Representations, 2021

2019

Partially Exchangeable Networks and Architectures for Learning Summary Statistics in Approximate Bayesian Computation.

Samuel Wiqvist, Pierre-Alexandre Mattei, Umberto Picchini, Jes Frellsen

Proceedings of the 36th International Conference on Machine Learning, 2019

MIWAE: Deep Generative Modelling and Imputation of Incomplete Data Sets.

Pierre-Alexandre Mattei, Jes Frellsen

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

missIWAE: Deep Generative Modelling and Imputation of Incomplete Data.

Pierre-Alexandre Mattei, Jes Frellsen

CoRR, 2018

Leveraging the Exact Likelihood of Deep Latent Variable Models.

Pierre-Alexandre Mattei, Jes Frellsen

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2016

Combining a relaxed EM algorithm with Occam's razor for Bayesian variable selection in high-dimensional regression.

Pierre Latouche, Pierre-Alexandre Mattei, Charles Bouveyron, Julien Chiquet

J. Multivar. Anal., 2016

Globally Sparse Probabilistic PCA.

Pierre-Alexandre Mattei, Charles Bouveyron, Pierre Latouche

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016