3 papers
cs.LG2026
Neural Galerkin Normalizing Flows for Bayesian Inference of Diffusions with Inaccessible Boundaries
Riccardo Saporiti, Fabio Nobile
One of the primary challenges in Bayesian inference on the parameters of a diffusion model from discrete observations is the unavailability of an analytical expression for the tran…
cs.LG2026
Neural Galerkin Normalizing Flow for Transition Probability Density Functions of Diffusion Models
Riccardo Saporiti, Fabio Nobile
We propose a new Neural Galerkin Normalizing Flow framework to approximate the transition probability density function of a diffusion process by solving the corresponding Fokker-Pl…
math.OC2024
An optimal control strategy to design passive thermal cloaks of arbitrary shape
Riccardo Saporiti, Carlo Sinigaglia, Andrea Manzoni +1
In this paper we describe a numerical framework for achieving passive thermal cloaking of arbitrary shapes in both static and transient regimes. The design strategy is cast as the…