Asymptotic-Preserving Neural Networks for multiscale hyperbolic models of epidemic spread

Asymptotic-Preserving Neural Networks for multiscale hyperbolic models of epidemic spread. Giulia Bertaglia, Chuan Lu, Lorenzo Pareschi, and Xueyu Zhu https://t.co/ZZiruDyrxy

scenarios confirms the validity of the proposed approach, highlighting the importance of the AP property in the neural network when dealing with multiscale problems especially in presence of sparse and partially observed systems. [8/8 of https://t.co/60…

hyperbolic transport models of epidemic spread that, thanks to an appropriate AP formulation of the loss function, is capable to work uniformly at the different scales of the system. A series of numerical tests for different epidemic [7/8 of https://t.c…

respect to the small scales, it is desirable that the neural network satisfies an Asymptotic-Preservation (AP) property in the learning process. To this end, we consider a new class of AP Neural Networks (APNNs) for multiscale [6/8 of https://t.co/605Jk…