| MIWAE: Deep Generative Modelling and Imputation of Incomplete Data Sets PA Mattei, J Frellsen International Conference on Machine Learning, 4413-4423, 2019 | 50 | 2019 |
| Leveraging the exact likelihood of deep latent variable models PA Mattei, J Frellsen Advances in Neural Information Processing Systems, 3855-3866, 2018 | 26 | 2018 |
| Bayesian variable selection for globally sparse probabilistic PCA C Bouveyron, P Latouche, PA Mattei Electronic Journal of Statistics 12 (2), 3036-3070, 2018 | 19 | 2018 |
| 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 | 12 | 2016 |
| Globally sparse probabilistic PCA PA Mattei, C Bouveyron, P Latouche Artificial Intelligence and Statistics, 976-984, 2016 | 10 | 2016 |
| Deep adversarial Gaussian mixture auto-encoder for clustering W Harchaoui, PA Mattei, C Bouveyron | 9 | 2017 |
| Exact dimensionality selection for Bayesian PCA C Bouveyron, P Latouche, PA Mattei Scandinavian Journal of Statistics 47 (1), 196-211, 2020 | 8 | 2020 |
| 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 | 7 | 2019 |
| Multiplying a Gaussian matrix by a Gaussian vector PA Mattei Statistics & Probability Letters 128, 67-70, 2017 | 6 | 2017 |
| 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 | 4 | 2019 |
| Refit your encoder when new data comes by PA Mattei, J Frellsen 3rd NeurIPS workshop on Bayesian Deep Learning, 2018 | 4 | 2018 |
| A parsimonious tour of bayesian model uncertainty PA Mattei arXiv preprint arXiv:1902.05539, 2019 | 3 | 2019 |
| Unobserved classes and extra variables in high-dimensional discriminant analysis M Fop, PA Mattei, TB Murphy, C Bouveyron CASI 2018 Conference proceeding, 70-72, 2018 | 2 | 2018 |
| not-MIWAE: Deep generative modelling with missing not at random data NB Ipsen, PA Mattei, J Frellsen arXiv preprint arXiv:2006.12871, 2020 | 1 | 2020 |
| Model selection for sparse high-dimensional learning PA Mattei | 1 | 2017 |
| Negative Dependence Tightens Variational Bounds PA Mattei, J Frellsen ICML 2020-2nd Workshop on Negative Dependence and Submodularity for ML, 2020 | | 2020 |
| 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 | | 2020 |
| Wasserstein Adversarial Mixture Clustering W Harchaoui, A Almansa, PA Mattei, C Bouveyron | | 2018 |
| Deep latent variable models PA Mattei Séminaire de statistique du CNAM, 2018 | | 2018 |
| Leveraging the Exact Likelihood of Deep Latent Variable Models–Appendices PA Mattei, J Frellsen Supplementary Material - NeurIPS 2018, 2018 | | 2018 |
Jes FrellsenAssociate Professor, Technical University of Denmark (DTU)Bestätigte E-Mail-Adresse bei dtu.dk
