2 citations · 2 across the 3 of their papers we have counts for
3 papers
Simulation of parametrized cardiac electrophysiology in three dimensions using physics-informed neural networks
Roshan Antony Gomez, Julien Stöcker, Barış Cansız +1
Physics-informed neural networks (PINNs) are extensively used to represent various physical systems across multiple scientific domains. The same can be said for cardiac electrophys…
Integration of physics-informed operator learning and finite element method for parametric learning of partial differential equations
Shahed Rezaei, Ahmad Moeineddin, Michael Kaliske +1
We present a method that employs physics-informed deep learning techniques for parametrically solving partial differential equations. The focus is on the steady-state heat equation…
Fast and Reliable Reduced-Order Models for Cardiac Electrophysiology
Sridhar Chellappa, Barış Cansız, Lihong Feng +2
Mathematical models of the human heart are increasingly playing a vital role in understanding the working mechanisms of the heart, both under healthy functioning and during disease…