most cited(H)DPGMM: A Hierarchy of Dirichlet Process Gaussian Mixture Models for the inference of the black hole mass function

45 citations · 45 across the 1 of their papers we have counts for

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astro-ph.IM2021★ 45 cited

(H)DPGMM: A Hierarchy of Dirichlet Process Gaussian Mixture Models for the inference of the black hole mass function

Stefano Rinaldi, Walter Del Pozzo

We introduce (H)DPGMM, a hierarchical Bayesian non-parametric method based on the Dirichlet Process Gaussian Mixture Model, designed to infer data-driven population properties of a…