Publications

Journals

• Ascolani, F., Damato, S. and Ruggiero, M. (2024) An R package for nonparametric inference on dynamic populations with infinitely many types Journal of Computational Biology, forthcoming (pdf).

• Ascolani, F. and Zanella, G. (2024) Dimension-free mixing times of Gibbs samplers for Bayesian hierarchical models. Annals of Statistics, 52(3), 869-894 (pdf).

• Ascolani, F., Franzolini, B., Lijoi, A. and Prünster, I. (2024) Nonparametric priors with full-range borrowing of information. Biometrika, 111(3), 945–969 (pdf).

• Ascolani, F., Lijoi, A., Rebaudo, G. and Zanella, G. (2023) Clustering consistency with Dirichlet process mixtures. Biometrika, 110(2), 551-558 (pdf).

• Ascolani, F., Lijoi, A. and Ruggiero, M. (2023) Smoothing distributions for conditional Fleming-Viot and Dawson-Watanabe diffusions. Bernoulli, 29(2), 1410-1434 (pdf).

• Ascolani, F., Lijoi, A. and Ruggiero, M. (2021) Predictive inference with Fleming-Viot driven dependent Dirichlet processes. Bayesian Analysis, 16(2), 371-395 (pdf).

Submitted

• Ascolani, F., Lavenant, H. and Zanella, G. (2024+) Entropy contraction of the Gibbs sampler under log-concavity. Submitted (pdf).

• Ascolani, F., Roberts, G. O. and Zanella, G. (2024+) Scalability of Metropolis-within-Gibbs schemes for high-dimensional Bayesian models. Submitted (pdf).

Ongoing Projects

• Ascolani, F., Lijoi, A. and Prünster, I. (2024+) Trees of random probability measures and Bayesian nonparametric modelling. Working Paper.

Discussions and Conference Proceedings

• Ascolani, F., Lijoi, A., Prünster, I. (2024). Discussion of Root and community inference on the latent growth process of a network by Crane, H. and Xu, M. J. R. Stat. Soc. Series B, 85 (5), 1357-1391.

• Ascolani, F., Lijoi, A., Prünster, I. (2023). Discussion of Martingale Posterior Distribution by Fong, E., Holmes, C and Walker, S. G. J. R. Stat. Soc. Series B, 85 (5), 1357-1391.

• Ascolani, F., Catalano, M., Prünster, I. (2022). Discussion of Evaluating sensitivity to the stick-breaking prior in Bayesian nonparametrics by Giordano, R., Liu, R., Jordan, M. I., and Broderick, T. Bayesian Anal., 1 (1), 1-34 (pdf).

• Ascolani, F. and Ghidini, V. (2023) Posterior clustering for Dirichlet Process Mixtures of Gaussians with constant data. Book of Short Papers CLADAG 2023, Pearson (pdf).

• Ascolani, F. and Ghidini, V. (2023) Linear models with assumptions-free residuals: a Bayesian Nonparametric approach Book of short papers SEAS IN 2023, Pearson (pdf).

• Ascolani, F. (2022) Mixing Times of a Gibbs Sampler for Probit Hierarchical Models. International Conference on Bayesian Statistics in Action, Springer (pdf).

• Ascolani, F., Franzolini, B., Lijoi, A. and Prünster, I. (2021) On the dependence structure in Bayesian nonparametric priors. Book of Short Papers of the Italian Statistical Society, Pearson (pdf).

• Ascolani, F., Lijoi, A. Ruggiero, M. and Prünster, I. (2021) A framework for filtering in hidden Markov models with normalized random measures. Book of Short Papers of the Italian Statistical Society, Pearson (pdf).