Filippo Ascolani

7 catalog papers. Identity-linked publications and additional name matches are distinguished below.

ORCID: 0009-0009-3899-8877

Department of Statistical Science, Duke University , Durham, NC 27708 , USA

Publications

• Scalability of Metropolis-within-Gibbs schemes for high-dimensional Bayesian models — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2026
• Mixing times of data-augmentation Gibbs samplers for high-dimensional probit regression — Journal of Machine Learning Research 2026 (name-matched, not ORCID-linked)
• Dimension-free mixing times of Gibbs samplers for Bayesian hierarchical models — The Annals of Statistics 2024
• Nonparametric priors with full-range borrowing of information — Biometrika 2024
• Filippo Ascolani, Antonio Lijoi and Igor Prünster’s contribution to the Discussion of ‘Root and community inference on the latent growth process of a network’ by Crane and Xu — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2024
• Filippo Ascolani, Antonio Lijoi, and Igor Prünster’s contribution to the Discussion of ‘Martingale Posterior Distributions’ by Fong, Holmes and Walker — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2023
• Clustering consistency with Dirichlet process mixtures — Biometrika 2023