Tommaso Rigon
Tommaso Rigon
Research Associate at Duke University
Verified email at duke.edu - Homepage
TitleCited byYear
Tractable Bayesian density regression via logit stick-breaking priors
T Rigon, D Durante
arXiv preprint arXiv:1701.02969, 2018
42018
Conditionally conjugate mean–field variational Bayes for logistic models
D Durante, T Rigon
Statistical Science 34 (3), 472-485, 2019
2*2019
A nested expectation–maximization algorithm for latent class models with covariates
D Durante, A Canale, T Rigon
Statistics & Probability Letters 146, 97-103, 2019
12019
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
12019
An enriched mixture model for functional clustering
T Rigon
arXiv preprint arXiv:1907.02493, 2019
2019
Finite-dimensional discrete random structures and Bayesian clustering
A Lijoi, I Prünster, T Rigon
Collegio Carlo Alberto, 2019
2019
The Pitman–Yor multinomial process for mixture modeling
A Lijoi, I Prünster, T Rigon
Collegio Carlo Alberto, 2019
2019
Logit stick-breaking priors for partially exchangeable count data
T Rigon
Book of short paper of the Italian statistical society, 2018
2018
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
2018
Dati funzionali di traffico telefonico: un approccio bayesiano non parametrico
T Rigon
Universitŕ degli studi di Padova, 2015
2015
Trasformazione Box Cox: un'analisi basata sulla verosimiglianza
T Rigon
Universitŕ degli studi di Padova, 2013
2013
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Articles 1–11