Search Results for author:
Found 4 papers, 3 papers with code
On the intrinsic dimensionality of Covid-19 data: a global perspective
This paper aims to develop a global perspective of the complexity of the relationship between the standardised per-capita growth rate of Covid-19 cases, deaths, and the OxCGRT Covid-19 Stringency Index, a measure describing a country's stringency of lockdown policies.
A Common Atom Model for the Bayesian Nonparametric Analysis of Nested Data
The use of high-dimensional data for targeted therapeutic interventions requires new ways to characterize the heterogeneity observed across subgroups of a specific population.
Methodology Applications
A Two-Stage Bayesian Semiparametric Model for Novelty Detection with Robust Prior Information
Novelty detection methods aim at partitioning the test units into already observed and previously unseen patterns.
Applications
Data segmentation based on the local intrinsic dimension
Here we develop a robust approach to discriminate regions with different local IDs and segment the points accordingly.
