8 citations · 9 across the 2 of their papers we have counts for
5 papers
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…
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…
Multivariate Species Sampling Models
Beatrice Franzolini, Antonio Lijoi, Igor Prünster +1
Species sampling processes have long served as the fundamental framework for modeling random discrete distributions and exchangeable sequences. However, data arising from distinct…
Scalable expectation propagation for generalized linear models
Niccolò Anceschi, Augusto Fasano, Beatrice Franzolini +1
Generalized linear models (GLMs) arguably represent the standard approach for statistical regression beyond the Gaussian likelihood scenario. When Bayesian formulations are employe…
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…