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12/04/2022
Variational Inference for Semiparametric Bayesian Novelty Detection in Large Datasets
After being trained on a fully-labeled training set, where the observati...
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05/02/2022
Multiple hypothesis screening using mixtures of non-local distributions
The analysis of large-scale datasets, especially in biomedical contexts,...
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03/08/2022
On the intrinsic dimensionality of Covid-19 data: a global perspective
This paper aims to develop a global perspective of the complexity of the...
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06/15/2021
A Horseshoe Pit mixture model for Bayesian screening with an application to light sheet fluorescence microscopy in brain imaging
Finding parsimonious models through variable selection is a fundamental ...
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04/28/2021
Distributional Results for Model-Based Intrinsic Dimension Estimators
Modern datasets are characterized by a large number of features that may...
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02/23/2021
intRinsic: an R package for model-based estimation of the intrinsic dimension of a dataset
The estimation of the intrinsic dimension of a dataset is a fundamental ...
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08/17/2020
A Common Atom Model for the Bayesian Nonparametric Analysis of Nested Data
The use of high-dimensional data for targeted therapeutic interventions ...
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06/16/2020
A Two-Stage Bayesian Nonparametric Model for Novelty Detection with Robust Prior Information
Standard novelty detection methods aim at bi-partitioning the test units...
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02/11/2020