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stat.ME2021
A Horseshoe mixture model for Bayesian screening with an application to light sheet fluorescence microscopy in brain imaging
Francesco Denti, Ricardo Azevedo, Chelsie Lo +4
In this paper, we focus on identifying differentially activated brain regions using a light sheet fluorescence microscopy - a recently developed technique for whole-brain imaging.…
stat.ME2021★ 3 cited
Distributional Results for Model-Based Intrinsic Dimension Estimators
Francesco Denti, Diego Doimo, Alessandro Laio +1
Modern datasets are characterized by a large number of features that may conceal complex dependency structures. To deal with this type of data, dimensionality reduction techniques…
stat.CO2021★ 1 cited
intRinsic: an R Package for Model-Based Estimation of the Intrinsic Dimension of a Dataset
Francesco Denti
This article illustrates intRinsic, an R package that implements novel state-of-the-art likelihood-based estimators of the intrinsic dimension of a dataset, an essential quantity f…