Dynamics-informed deconvolutional neural networks for super-resolution identification of regime changes in epidemiological time series
Description
The ability to infer the timing and amplitude of perturbations in epidemiological systems from their stochastically spread low-resolution outcomes is crucial for multiple applications. However, the general problem of connecting epidemiological curves
