Search Results for author: Arturo Castellanos

Found 1 papers, 0 papers with code

Fast kernel half-space depth for data with non-convex supports

no code implementations21 Dec 2023 Arturo Castellanos, Pavlo Mozharovskyi, Florence d'Alché-Buc, Hicham Janati

Data depth is a statistical function that generalizes order and quantiles to the multivariate setting and beyond, with applications spanning over descriptive and visual statistics, anomaly detection, testing, etc.

Anomaly Detection Descriptive

Cannot find the paper you are looking for? You can Submit a new open access paper.