Pierre-Alexandre Mattei
Pierre-Alexandre Mattei
Research scientist, Inria
Verified email at inria.fr - Homepage
Cited by
Cited by
MIWAE: Deep Generative Modelling and Imputation of Incomplete Data Sets
PA Mattei, J Frellsen
International Conference on Machine Learning, 4413-4423, 2019
Leveraging the exact likelihood of deep latent variable models
PA Mattei, J Frellsen
Advances in Neural Information Processing Signals 31, 3859-3870, 2018
Bayesian variable selection for globally sparse probabilistic PCA
C Bouveyron, P Latouche, PA Mattei
Electronic Journal of Statistics 12 (2), 3036-3070, 2018
Deep adversarial Gaussian mixture auto-encoder for clustering
W Harchaoui, PA Mattei, C Bouveyron
Partially Exchangeable Networks and Architectures for Learning Summary Statistics in Approximate Bayesian Computation
S Wiqvist, PA Mattei, U Picchini, J Frellsen
International Conference on Machine Learning, 6798-6807, 2019
Combining a relaxed EM algorithm with Occam’s razor for Bayesian variable selection in high-dimensional regression
P Latouche, PA Mattei, C Bouveyron, J Chiquet
Journal of Multivariate Analysis 146, 177-190, 2016
Exact dimensionality selection for Bayesian PCA
C Bouveyron, P Latouche, PA Mattei
Scandinavian Journal of Statistics 47 (1), 196-211, 2020
Globally sparse probabilistic PCA
PA Mattei, C Bouveyron, P Latouche
Artificial Intelligence and Statistics, 976-984, 2016
Refit your encoder when new data comes by
PA Mattei, J Frellsen
3rd NeurIPS workshop on Bayesian Deep Learning, 2018
Multiplying a Gaussian matrix by a Gaussian vector
PA Mattei
Statistics & Probability Letters 128, 67-70, 2017
not-MIWAE: Deep generative modelling with missing not at random data
NB Ipsen, PA Mattei, J Frellsen
International Conference on Learning Representations, 2021
A parsimonious tour of bayesian model uncertainty
PA Mattei
arXiv preprint arXiv:1902.05539, 2019
Class‐specific variable selection in high‐dimensional discriminant analysis through Bayesian Sparsity
F Orlhac, PA Mattei, C Bouveyron, N Ayache
Journal of Chemometrics 33 (2), e3097, 2019
Unobserved classes and extra variables in high-dimensional discriminant analysis
M Fop, PA Mattei, C Bouveyron, TB Murphy
arXiv preprint arXiv:2102.01982, 2021
How to deal with missing data in supervised deep learning?
N Ipsen, PA Mattei, J Frellsen
ICML Workshop on the Art of Learning with Missing Values (Artemiss), 2020
Wasserstein Adversarial Mixture for Deep Generative Modeling and Clustering
W Harchaoui, PA Mattei, A Almansa, C Bouveyron
Model selection for sparse high-dimensional learning
PA Mattei
Université Paris 5, 2017
Tensor decomposition for learning Gaussian mixtures from moments
R Khouja, PA Mattei, B Mourrain
arXiv preprint arXiv:2106.00555, 2021
Negative Dependence Tightens Variational Bounds
PA Mattei, J Frellsen
ICML 2020-2nd Workshop on Negative Dependence and Submodularity for ML, 2020
Wasserstein Adversarial Mixture Clustering
W Harchaoui, A Almansa, PA Mattei, C Bouveyron
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