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math.NA2025
Learning cardiac activation and repolarization times with operator learning
Edoardo Centofanti, Giovanni Ziarelli, Nicola Parolini +3
Solving partial or ordinary differential equation models in cardiac electrophysiology is a computationally demanding task, particularly when high-resolution meshes are required to…
math.NA2024
A posteriori error analysis for a coupled Stokes-poroelastic system with multiple compartments
Ivan Fumagalli, Nicola Parolini, Marco Verani
The discretization of fluid-poromechanics systems is typically highly demanding in terms of computational effort. This is particularly true for models of multiphysics flows in the…
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…