Pierre-Alexandre Mattei
Pierre-Alexandre Mattei
Postdoctoral fellow, IT University of Copenhagen
Adresse e-mail validée de itu.dk - Page d'accueil
TitreCitée parAnnée
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
112016
Bayesian variable selection for globally sparse probabilistic PCA
C Bouveyron, P Latouche, PA Mattei
Electronic Journal of Statistics 12 (2), 3036-3070, 2018
92018
Globally sparse probabilistic PCA
PA Mattei, C Bouveyron, P Latouche
Artificial Intelligence and Statistics, 976-984, 2016
62016
Leveraging the Exact Likelihood of Deep Latent Variables Models
PA Mattei, J Frellsen
arXiv preprint arXiv:1802.04826, 2018
52018
Exact dimensionality selection for Bayesian PCA
C Bouveyron, P Latouche, PA Mattei
arXiv preprint arXiv:1703.02834, 2017
52017
Multiplying a Gaussian matrix by a Gaussian vector
PA Mattei
Statistics & Probability Letters 128, 67-70, 2017
42017
Deep adversarial gaussian mixture auto-encoder for clustering
W Harchaoui, PA Mattei, C Bouveyron
42017
Class-specific Variable Selection in High-Dimensional Discriminant Analysis through Bayesian Sparsity
F Orlhac, PA Mattei, C Bouveyron, N Ayache
12018
Model selection for sparse high-dimensional learning
PA Mattei
Université Paris 5, 2017
12017
missIWAE: Deep Generative Modelling and Imputation of Incomplete Data
PA Mattei, J Frellsen
arXiv preprint arXiv:1812.02633, 2018
2018
Wasserstein Adversarial Mixture Clustering
W Harchaoui, PA Mattei, A Alamansa, C Bouveyron
2018
Refit your Encoder when New Data Comes by
PA Mattei, J Frellsen
2018
Wasserstein Adversarial Mixture for Deep Generative Modeling and Clustering
W Harchaoui, PA Mattei, A Almansa, C Bouveyron
Leveraging the Exact Likelihood of Deep Latent Variable Models–Appendices
PA Mattei, J Frellsen
Unobserved classes and extra variables in high-dimensional discriminant analysis
M Fop, PA Mattei, TB Murphy, C Bouveyron
CASI 2018, 70, 0
Sélection de modèles parcimonieux pour l’apprentissage statistique en grande dimension
PA Mattei
Une relaxation continue du rasoir d’Ockham pour la régression en grande dimension
PA Mattei, P Latouche, C Bouveyron, J Chiquet
Analyse en composantes principales globalement parcimonieuse
PA Mattei, C Bouveyron, P Latouche
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