Publications
Franzolini, B. , Lijoi, A., and Prünster, I. (2023).
Model selection for maternal hypertensive disorders with symmetric hierarchical Dirichlet processes.
The Annals of Applied Statistics 17(1): 313-332. DOI:10.1214/22-AOAS1628
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Franzolini, B. Cremaschi, A., van den Boom, W., and De Iorio, M. (2023).
Bayesian clustering of multiple zero-inflated outcomes. Philosophical Transactions of the Royal Society A, 81(2247): 20220145.
DOI:10.1098/rsta.2022.0145
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Franzolini, B. Beskos, A., De Iorio, M., Poklewski Koziell, W., and Grzeszkiewicz, K. (2022).
Change point detection in dynamic Gaussian graphical models: the impact of COVID-19 pandemic on the US stock market.
arXiv:2208.00952
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Refereed discussions and conference proceedings
Fasano, A., Anceschi, N.,
Franzolini, B., and Rebaudo, G. (2023).
Efficient computation of predictive probabilities in probit models via expectation propagation.
In Book of Short Papers SIS 2023, in press.
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Rebaudo G., Fasano, A.,
Franzolini, B., and Müller, P. (2023)
A discussion on: “Evaluating sensitivity to the stick-breaking prior in Bayesian nonparametrics” by Giordano, R., Liu, R., Jordan M. I. and Broderick T.
Bayesian Analysis, 18(1): 287-366. DOI: 10.1214/22-BA1309 [
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Franzolini, B. and Rebaudo, G. (2022).
A regularized-entropy estimator to enhance cluster interpretability in Bayesian nonparametrics.
In Book of Short Papers SIS 2022, (Editors: Balzanella, A., Bini, M., Cavicchia, C. and Verde, R.) ISBN 9788891932310
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Ascolani, F.,
Franzolini, B. , Lijoi, A., and Prünster, I. (2021).
On the dependence structure in Bayesian nonparametric priors.
In Book of Short Papers SIS 2021, (Editors: Perna, C., Salvati, N. and Schirripa Spagnolo, F.) ISBN 9788891927361
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PhD Thesis
Franzolini, B. (Advisors: Lijoi, A., and Prünster, I.), Feb 2022.
On Dependent Processes in Bayesian Nonparametrics: Theory, Methods, and Applications. Bocconi University [
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