Pierre-Alexandre Mattei

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Jes FrellsenAssociate Professor, Technical University of Denmark (DTU)Verified email at dtu.dk
Charles BouveyronProfessor of Statistics & AI, Director of Institut 3IA Côte d'Azur, Inria, Université Côte d'AzurVerified email at inria.fr
Pierre LatoucheLaboratoire LMBP, Université Clermont AuvergneVerified email at math.cnrs.fr
Hugo SchmutzPhd student, INRIA, Université côte d'AzurVerified email at inria.fr
Benoit CarryLagrange, Observatoire de la Côte d'AzurVerified email at oca.eu
Warith HarchaouiDERAISON.aiVerified email at deraison.ai
Niels IpsenTechnical University of DenmarkVerified email at dtu.dk
Olivier HumbertPU-PH, Centre Antoine Lacassagne, université Côte d'Azur, NiceVerified email at unice.fr
Frédéric PreciosoUniversite Cote d'AzurVerified email at unice.fr
Julien ChiquetUniversité Paris-Saclay, INRAE, AgroParisTechVerified email at inrae.fr
Louis OhlPhD Student, Université Côte d'Azur, Inria, CNRS, I3S, Maasai team, CHU de Québec, Research CenterVerified email at kth.se
Hugo SenetaireTechnical University of DenmarkVerified email at dtu.dk
Umberto PicchiniDept. Mathematical Sciences, University of Gothenburg and Chalmers University of TechnologyVerified email at chalmers.se
Mickael LeclercqPhD Computer Science & BioinformaticsVerified email at mail.mcgill.ca
Federico BergaminTechnical University of DenmarkVerified email at dtu.dk
Fanny OrlhacLITO, Inserm, Institut CurieVerified email at inserm.fr
Nicholas AyacheResearch Director at INRIA/ CSO of 3IA Côte d'AzurVerified email at inria.fr
Brendan MurphyUniversity College DublinVerified email at ucd.ie
Michael FopLecturer/Assistant Professor University College DublinVerified email at ucd.ie

Pierre-Alexandre Mattei

Research scientist, Inria

Verified email at inria.fr - Homepage

Statistics Machine learning Latent variable models Deep generative models


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MIWAE: Deep Generative Modelling and Imputation of Incomplete Data Sets PA Mattei, J Frellsen International Conference on Machine Learning, 4413-4423, 2019	254	2019
Leveraging the exact likelihood of deep latent variable models PA Mattei, J Frellsen Advances in Neural Information Processing Signals 31, 3859-3870, 2018	65	2018
not-MIWAE: Deep generative modelling with missing not at random data NB Ipsen, PA Mattei, J Frellsen International Conference on Learning Representations, 2021	55	2021
How to deal with missing data in supervised deep learning? N Ipsen, PA Mattei, J Frellsen International Conference on Learning Representations, 2022	38	2022
Asteroid taxonomy from cluster analysis of spectrometry and albedo M Mahlke, B Carry, PA Mattei Astronomy & Astrophysics 665, A26, 2022	36	2022
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	36	2019
Deep adversarial Gaussian mixture auto-encoder for clustering W Harchaoui, PA Mattei, C Bouveyron OpenReview preprint, 2017	31	2017
Bayesian variable selection for globally sparse probabilistic PCA C Bouveyron, P Latouche, PA Mattei Electronic Journal of Statistics 12 (2), 3036-3070, 2018	30	2018
Exact dimensionality selection for Bayesian PCA C Bouveyron, P Latouche, PA Mattei Scandinavian Journal of Statistics 47 (1), 196-211, 2020	23	2020
Globally sparse probabilistic PCA PA Mattei, C Bouveyron, P Latouche International Conference on Artificial Intelligence and Statistics, 976-984, 2016	16	2016
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	16	2016
A parsimonious tour of bayesian model uncertainty PA Mattei arXiv preprint arXiv:1902.05539, 2019	15	2019
Model-agnostic out-of-distribution detection using combined statistical tests F Bergamin, PA Mattei, JD Havtorn, H Senetaire, H Schmutz, L Maaløe, ... International Conference on Artificial Intelligence and Statistics, 10753-10776, 2022	12	2022
Refit your encoder when new data comes by PA Mattei, J Frellsen 3rd NeurIPS workshop on Bayesian Deep Learning, 2018	11	2018
Tensor decomposition for learning Gaussian mixtures from moments R Khouja, PA Mattei, B Mourrain Journal of Symbolic Computation 113, 193-210, 2022	9	2022
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	9	2019
Multiplying a Gaussian matrix by a Gaussian vector PA Mattei Statistics & Probability Letters 128, 67-70, 2017	9	2017
Don’t fear the unlabelled: safe semi-supervised learning via debiasing H Schmutz, O Humbert, PA Mattei International Conference on Learning Representations, 2023	8*	2023
Generalised mutual information for discriminative clustering L Ohl, PA Mattei, C Bouveyron, W Harchaoui, M Leclercq, A Droit, ... Advances in Neural Information Processing Systems 35, 3377-3390, 2022	3	2022
Unobserved classes and extra variables in high-dimensional discriminant analysis M Fop, PA Mattei, C Bouveyron, TB Murphy Advances in Data Analysis and Classification 16 (1), 55-92, 2022	3	2022

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