7 papers
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…
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…
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…
Block BDDC/FETI-DP Preconditioners for Three-Field mixed finite element Discretizations of Biot's consolidation model
Hanyu Chu, Luca Franco Pavarino, Stefano Zampini
In this paper, we construct and analyze a block dual-primal preconditioner for Biot's consolidation model approximated by three-field mixed finite elements based on a displacement,…
Parameter Robust Isogeometric Methods for a Four-Field Formulation of Biot's Consolidation Model
Hanyu Chu, Luca Franco Pavarino
In this paper, a novel isogeometric method for Biot's consolidation model is constructed and analyzed, using a four-field formulation where the unknown variables are the solid disp…
Convergence analysis of BDDC preconditioners for composite DG discretizations of the cardiac cell-by-cell model
Ngoc Mai Monica Huynh, Fatemeh Chegini, Luca Franco Pavarino +2
A Balancing Domain Decomposition by Constraints (BDDC) preconditioner is constructed and analyzed for the solution of composite Discontinuous Galerkin discretizations of reaction-d…