Education
PhD in Statistics, Bocconi University, 2021
Research Interests
Bayesian Data Analysis, Computational Statistics, Epidemiology
Affiliation
Tenure-track Assistant Professor of Statistics, University of Torino
Selected Works
- Anceschi, N., Fasano, A., Durante, D., and Zanella, G. (2023). Bayesian conjugacy in probit, tobit, multinomial probit and extensions: a review and new results. Journal of the American Statistical Association, 118(542), 1451-1469.
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Fasano, A., Durante, D., and Zanella, G. (2022). Scalable and accurate variational Bayes for high-dimensional binary
regression models. Biometrika, 109(4), 901-919. -
Fasano, A., and Durante, D. (2022). A class of conjugate priors for multinomial probit models which includes the multivariate normal one.
Journal of Machine Learning Research, 23(30), 1-16.
