1 citations · 1 across the 7 of their papers we have counts for
7 papers
Bayesian nonparametric modeling of multivariate count data with an unknown number of traits
Lorenzo Ghilotti, Federico Camerlenghi, Tommaso Rigon +1
Feature and trait allocation models are fundamental objects in Bayesian nonparametrics and play a prominent role in several applications. Existing approaches, however, typically as…
Hierarchical shot-noise Cox process mixtures for clustering across groups
Alessandro Carminati, Mario Beraha, Federico Camerlenghi +1
Clustering observations across partially exchangeable groups of data is a routine task in Bayesian nonparametrics. Previously proposed models allow for clustering across groups by…
Repulsive Mixture Model with Projection Determinantal Point Process
Ziyi Song, Federico Camerlenghi, Weining Shen +2
In many scientific domains, clustering aims to reveal interpretable latent structure that reflects relevant subpopulations or processes. Widely used Bayesian mixture models for mod…
Palm distributions of superposed point processes for statistical inference
Mario Beraha, Federico Camerlenghi, Lorenzo Ghilotti
Palm distributions play a central role in the study of point processes and their associated summary statistics. In this paper, we characterize the Palm distributions of the superpo…
Extended feature allocation models
Mario Beraha, Federico Camerlenghi, Lorenzo Ghilotti
Feature allocation models are Bayesian nonparametric tools tailored to data in which each observation can simultaneously exhibit multiple characteristics, or features. A fundamenta…
On the Palm distribution of superposition of point processes
Mario Beraha, Federico Camerlenghi
Palm distributions are critical in the study of point processes. In the present paper we focus on a point process defined as the superposition, i.e., sum, of two independent po…