5 citations · 5 across the 3 of their papers we have counts for
3 papers
Physics-Informed Neural Networks can accurately model cardiac electrophysiology in 3D geometries and fibrillatory conditions
Ching-En Chiu, Aditi Roy, Sarah Cechnicka +6
Physics-Informed Neural Networks (PINNs) are fast becoming an important tool to solve differential equations rapidly and accurately, and to identify the systems parameters that bes…
A nonparametric test for diurnal variation in spot correlation processes
Kim Christensen, Ulrich Hounyo, Zhi Liu
The association between log-price increments of exchange-traded equities, as measured by their spot correlation estimated from high-frequency data, exhibits a pronounced upward-slo…
Characterisation of Anti-Arrhythmic Drug Effects on Cardiac Electrophysiology using Physics-Informed Neural Networks
Ching-En Chiu, Arieh Levy Pinto, Rasheda A Chowdhury +2
The ability to accurately infer cardiac electrophysiological (EP) properties is key to improving arrhythmia diagnosis and treatment. In this work, we developed a physics-informed n…