31 citations · 78 across the 14 of their papers we have counts for
7 papers · 1 filter
Entropy regularization in probabilistic clustering
Beatrice Franzolini, Giovanni Rebaudo
Bayesian nonparametric mixture models are widely used to cluster observations. However, one major drawback of the approach is that the estimated partition often presents unbalanced…
Graph-Aligned Random Partition Model (GARP)
Giovanni Rebaudo, Peter Mueller
Bayesian nonparametric mixtures and random partition models are powerful tools for probabilistic clustering. However, standard independent mixture models can be restrictive in some…
Bayesian Mixed Multidimensional Scaling for Auditory Processing
Giovanni Rebaudo, Fernando Llanos, Bharath Chandrasekaran +1
The human brain distinguishes speech sounds by mapping acoustic signals into a latent perceptual space. This space can be estimated via multidimensional scaling (MDS), preserving t…
Bayesian Inference for the Multinomial Probit Model under Gaussian Prior Distribution
Augusto Fasano, Giovanni Rebaudo, Niccolò Anceschi
Multinomial probit (mnp) models are fundamental and widely-applied regression models for categorical data. Fasano and Durante (2022) proved that the class of unified skew-normal di…
Flexible clustering via hidden hierarchical Dirichlet priors
Antonio Lijoi, Igor Prünster, Giovanni Rebaudo
The Bayesian approach to inference stands out for naturally allowing borrowing information across heterogeneous populations, with different samples possibly sharing the same distri…
Separate Exchangeability as Modeling Principle in Bayesian Nonparametrics
Giovanni Rebaudo, Qiaohui Lin, Peter Mueller
We argue for the use of separate exchangeability as a modeling principle in Bayesian nonparametric (BNP) inference. Separate exchangeability is \emph{de facto} widely applied in th…
A closed-form filter for binary time series
Augusto Fasano, Giovanni Rebaudo, Daniele Durante +1
Non-Gaussian state-space models arise in several applications, and within this framework the binary time series setting provides a relevant example. However, unlike for Gaussian st…