3 papers
math.NA2026
A Neural Latent Dynamics Approach for Solving Inverse Problems in Cardiac Electrophysiology
Edoardo Centofanti, Giovanni Ziarelli, Simone Scacchi +1
Solving inverse problems in cardiac electrophysiology consists in the recovery of physiological parameters from surface electrocardiogram (ECG) measurements, a task which is often…
cs.LG2025
Learning High-dimensional Ionic Model Dynamics Using Fourier Neural Operators
Luca Pellegrini, Massimiliano Ghiotto, Edoardo Centofanti +1
Ionic models, described by systems of stiff ordinary differential equations, are fundamental tools for simulating the complex dynamics of excitable cells in both Computational Neur…
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…