| Feature selection via mutual information: New theoretical insights M Beraha, AM Metelli, M Papini, A Tirinzoni, M Restelli 2019 international joint conference on neural networks (IJCNN), 1-9, 2019 | 119 | 2019 |
| The semi-hierarchical Dirichlet process and its application to clustering homogeneous distributions M Beraha, A Guglielmi, FA Quintana Bayesian Analysis 16 (4), 1187-1219, 2021 | 30 | 2021 |
| MCMC computations for Bayesian mixture models using repulsive point processes M Beraha, R Argiento, J Møller, A Guglielmi Journal of Computational and Graphical Statistics 31 (2), 422-435, 2022 | 25 | 2022 |
| Projected statistical methods for distributional data on the real line with the Wasserstein metric M Pegoraro, M Beraha Journal of Machine Learning Research 23 (37), 1-59, 2022 | 18 | 2022 |
| JAGS, NIMBLE, Stan: a detailed comparison among Bayesian MCMC software M Beraha, D Falco, A Guglielmi arXiv preprint arXiv:2107.09357, 2021 | 14 | 2021 |
| Bayesian clustering of high-dimensional data via latent repulsive mixtures L Ghilotti, M Beraha, A Guglielmi Biometrika, asae059, 2024 | 7 | 2024 |
| Spatially dependent mixture models via the logistic multivariate CAR prior M Beraha, M Pegoraro, R Peli, A Guglielmi Spatial Statistics 46, 100548, 2021 | 7 | 2021 |
| Wasserstein principal component analysis for circular measures M Beraha, M Pegoraro Statistics and Computing 34 (5), 171, 2024 | 5 | 2024 |
| Normalised latent measure factor models M Beraha, JE Griffin Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2023 | 5 | 2023 |
| Bayesmix: Bayesian mixture models in C++ M Beraha, B Guindani, M Gianella, A Guglielmi arXiv preprint arXiv:2205.08144, 2022 | 5 | 2022 |
| Transform-scaled process priors for trait allocations in Bayesian nonparametrics M Beraha, S Favaro arXiv preprint arXiv:2303.17844, 2023 | 4 | 2023 |
| Improved prediction of future user activity in online A/B testing L Masoero, M Beraha, T Richardson, S Favaro arXiv preprint arXiv:2402.03231, 2024 | 3 | 2024 |
| A nonparametric Bayes approach to online activity prediction M Beraha, L Masoero, S Favaro, TS Richardson arXiv preprint arXiv:2401.14722, 2024 | 3 | 2024 |
| Normalized random meaures with interacting atoms for Bayesian nonparametric mixtures M Beraha, R Argiento, F Camerlenghi, A Guglielmi arXiv preprint arXiv:2302.09034 25, 2023 | 3 | 2023 |
| Fast pca in 1-d wasserstein spaces via b-splines representation and metric projection M Pegoraro, M Beraha Proceedings of the AAAI Conference on Artificial Intelligence 35 (10), 9342-9349, 2021 | 3 | 2021 |
| Childhood obesity in Singapore: A Bayesian nonparametric approach M Beraha, A Guglielmi, FA Quintana, M De Iorio, JG Eriksson, F Yap Statistical Modelling 24 (6), 541-560, 2024 | 2 | 2024 |
| MCMC for Bayesian nonparametric mixture modeling under differential privacy M Beraha, S Favaro, V Rao Journal of Computational and Graphical Statistics, 1-11, 2024 | 2 | 2024 |
| Random measure priors in Bayesian recovery from sketches M Beraha, S Favaro, M Sesia Journal of Machine Learning Research 25 (249), 1-53, 2024 | 2 | 2024 |
| Bayesian Nonparametric Vector Autoregressive Models via a Logit Stick-breaking Prior: an Application to Child Obesity M Beraha, A Guglielmi, FA Quintana, M de Iorio, JG Eriksson, F Yap arXiv preprint arXiv:2203.12280, 2022 | 2 | 2022 |
| Bayesian block-diagonal graphical models via the Fiedler prior J Arbel, M Beraha, D Bystrova SFdS-52 Journées de Statistique de la Société Francaise de Statistique, 1-6, 2021 | 2 | 2021 |
Alessandra GuglielmiProfessor of Statistics, Department of Mathematics, Politecnico di MilanoZweryfikowany adres z polimi.it
