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q-bio.QM2024
A model learning framework for inferring the dynamics of transmission rate depending on exogenous variables for epidemic forecasts
Giovanni Ziarelli, Stefano Pagani, Nicola Parolini +2
In this work, we aim to formalize a novel scientific machine learning framework to reconstruct the hidden dynamics of the transmission rate, whose inaccurate extrapolation can sign…
math.NA2024
Learning epidemic trajectories through Kernel Operator Learning: from modelling to optimal control
Giovanni Ziarelli, Nicola Parolini, Marco Verani
Since infectious pathogens start spreading into a susceptible population, mathematical models can provide policy makers with reliable forecasts and scenario analyses, which can be…