Nicolás Moreno

Uncertainty Quantification of State Variables Trajectories in the Context of Inverse Problems: An Approach from Bayesian Inference and FDA

This article proposes a methodology that combines tools of Bayesian inference, with Hamiltonian Monte Carlo sampling employed for efficient posterior exploration, and functional data analysis, to determine credible regions for the trajectories of the state variables throughout the time horizon of interest.