Experimental evidence of effective human–AI collaboration in medical decision-making C Reverberi, T Rigon, A Solari, C Hassan, P Cherubini, A Cherubini Scientific reports 12 (1), 14952, 2022 | 73 | 2022 |
Conditionally conjugate mean–field variational Bayes for logistic models D Durante, T Rigon Statistical Science 34 (3), 472-485, 2019 | 39 | 2019 |
Tractable Bayesian density regression via logit stick-breaking priors T Rigon, D Durante Journal of Statistical Planning and Inference 211, 131-142, 2021 | 32 | 2021 |
A generalized Bayes framework for probabilistic clustering T Rigon, AH Herring, DB Dunson Biometrika 110 (3), 559–578, 2023 | 25 | 2023 |
The Pitman–Yor multinomial process for mixture modeling A Lijoi, I Prünster, T Rigon Biometrika 107 (4), 891-906, 2020 | 25 | 2020 |
Extended stochastic block models with application to criminal networks S Legramanti, T Rigon, D Durante, DB Dunson The Annals of Applied Statistics 16 (4), 2369-2395, 2022 | 19 | 2022 |
Finite-dimensional discrete random structures and Bayesian clustering A Lijoi, I Prünster, T Rigon Journal of the American Statistical Association, 2023 | 15 | 2023 |
A nested expectation–maximization algorithm for latent class models with covariates D Durante, A Canale, T Rigon Statistics & Probability Letters 146, 97-103, 2019 | 9 | 2019 |
Bayesian testing for exogenous partition structures in stochastic block models S Legramanti, T Rigon, D Durante Sankhya A: The Indian Journal of Statistics 84, 108-126, 2020 | 6 | 2020 |
An enriched mixture model for functional clustering T Rigon Applied Stochastic Models in Business and Industry 39, 232--250, 2023 | 4 | 2023 |
Bayesian semiparametric modelling of contraceptive behavior in India via sequential logistic regressions T Rigon, D Durante, N Torelli Journal of the Royal Statistical Society. Series A, Statistics in Society …, 2019 | 4 | 2019 |
Sampling hierarchies of discrete random structures A Lijoi, I Prünster, T Rigon Statistics and Computing 30 (6), 1591-1607, 2020 | 3 | 2020 |
Hierarchical Spatio-Temporal Modeling of Resting State fMRI Data A Caponera, F Denti, T Rigon, A Sottosanti, A Gelfand Studies in Neural Data Science, 111-130, 2018 | 3 | 2018 |
Bayesian inference for generalized linear models via quasi-posteriors D Agnoletto, T Rigon, DB Dunson arXiv preprint arXiv:2311.00820, 2023 | 2 | 2023 |
Conjugate priors and bias reduction for logistic regression models T Rigon, E Aliverti Statistics & Probability Letters 202, 109901, 2023 | 2 | 2023 |
Bayesian nonparametric modeling of latent partitions via Stirling-gamma priors A Zito, T Rigon, DB Dunson arXiv preprint arXiv:2306.02360, 2023 | 2 | 2023 |
Bayesian modelling of sequential discoveries A Zito, T Rigon, O Ovaskainen, DB Dunson Journal of the American Statistical Association 118 (544), 2521–2532, 2023 | 2* | 2023 |
Inferring taxonomic placement from DNA barcoding aiding in discovery of new taxa A Zito, T Rigon, DB Dunson Methods in Ecology and Evolution 14 (2), 529-542, 2023 | 2 | 2023 |
Bayesian modeling via discrete nonparametric priors M Catalano, A Lijoi, I Prünster, T Rigon Japanese Journal of Statistics and Data Science 6, 607–624, 2023 | 1 | 2023 |
Bayesian nonparametric disclosure risk assessment S Favaro, F Panero, T Rigon Electronic Journal of Statistics 15 (2), 5626-5651, 2021 | 1 | 2021 |