59 citations · 217 across the 22 of their papers we have counts for
3 papers · 1 filter
An eikonal model with re-excitability for fast simulations in cardiac electrophysiology
Lia Gander, Rolf Krause, Francisco Sahli Costabal +1
Precision cardiology based on cardiac digital twins requires accurate simulations of cardiac arrhythmias. However, detailed models, such as the monodomain model, are computationall…
Generative Hyperelasticity with Physics-Informed Probabilistic Diffusion Fields
Vahidullah Tac, Manuel K Rausch, Ilias Bilionis +2
Many natural materials exhibit highly complex, nonlinear, anisotropic, and heterogeneous mechanical properties. Recently, it has been demonstrated that data-driven strain energy fu…
Physics-informed neural networks for blood flow inverse problems
Jeremias Garay, Jocelyn Dunstan, Sergio Uribe +1
Physics-informed neural networks (PINNs) have emerged as a powerful tool for solving inverse problems, especially in cases where no complete information about the system is known a…