Speaker
Alessandro Morandini
(SISSA)
Description
We introduce a new density estimator based on Markov Chains. This estimator presents several benefits with respect to the usual ones and can be used straightforwardly in all density-based approaches to data science. After showing its consistency, we will present some promising results when applied to general scope datasets. Finally, we perform a preliminary analysis of a subset of the latest high energy physics dataset from darkmachines, establishing encouraging prospects for future use.
Primary authors
Alessandro Morandini
(SISSA)
Andrea De Simone
(SISSA)
