1 citations · 1 across the 7 of their papers we have counts for
3 papers · 1 filter
A fast non-reversible sampler for Bayesian mixture models
Filippo Ascolani, Giacomo Zanella, Paolo Manildo
Mixtures models are a cornerstone of Bayesian modelling, and it is well-known that sampling from the resulting posterior distribution can be a hard task. In particular, popular rev…
Mixing times of data-augmentation Gibbs samplers for high-dimensional probit regression
Filippo Ascolani, Giacomo Zanella
We investigate the convergence properties of popular data-augmentation samplers for Baye\-sian probit regression. Leveraging recent results on Gibbs samplers for log-concave target…
Scalability of Metropolis-within-Gibbs schemes for high-dimensional Bayesian models
Filippo Ascolani, Gareth O. Roberts, Giacomo Zanella
We study general coordinate-wise MCMC schemes (such as Metropolis-within-Gibbs samplers), which are commonly used to fit Bayesian non-conjugate hierarchical models. We relate their…