Bayesian inferences of Skyrme Energy Density Functionals

Nuclear Density Functional Theory (DFT) is the microscopic nu­clear model with the broadest range of applicability; at the same time, several ways to parameterise an Energy Density Functional (EDF) exist, and improve­ments in the performances of the different EDFs seem to have slowed down in recent years. In this contribution, results of different Bayesian inferences of the Skyrme parameters will be discussed; in particular, we will focus on the differences related to the use of different target observables.