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DENSe: Bayesian density estimation for Poisson data

Posted: Mon May 31, 2021 5:39 pm
by Ada Coda
DENSe: Bayesian density estimation for Poisson data

Abstract: DENSe is a compact library to enable Bayesian non-parametric inferences of densities of Poisson data counts. Its framework of stateless methods is written in Python, although it relies on Numerical Information Field Theory (NIFTy) for the heavy lifting. DENSe aims at utilizing all the available information in the data by modeling the inherent correlation structure using a Matérn kernel. The inference of the density from count data can be written in a single line of python code. The fitting method takes a multidimensional numpy array as input and returns multidimensional arrays of the same dimensions encoding the density field.

Credit: Edenhofer, Gordian; Enßlin, Torsten; Frank, Philipp; Guardiani, Matteo; Roth, Jakob

Site: https://gitlab.mpcdf.mpg.de/ift/public/dense
https://arxiv.org/abs/2105.13483