22 citations · 44 across the 5 of their papers we have counts for
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REMuS-GNN: A Rotation-Equivariant Model for Simulating Continuum Dynamics
Mario Lino, Stati Fotiadis, Anil A. Bharath +1
Numerical simulation is an essential tool in many areas of science and engineering, but its performance often limits application in practice or when used to explore large parameter…
Simulating Continuum Mechanics with Multi-Scale Graph Neural Networks
Mario Lino, Chris Cantwell, Anil A. Bharath +1
Continuum mechanics simulators, numerically solving one or more partial differential equations, are essential tools in many areas of science and engineering, but their performance…
Simulating Surface Wave Dynamics with Convolutional Networks
Mario Lino, Chris Cantwell, Stathi Fotiadis +2
We investigate the performance of fully convolutional networks to simulate the motion and interaction of surface waves in open and closed complex geometries. We focus on a U-Net ar…
Comparing recurrent and convolutional neural networks for predicting wave propagation
Stathi Fotiadis, Eduardo Pignatelli, Mario Lino Valencia +3
Dynamical systems can be modelled by partial differential equations and numerical computations are used everywhere in science and engineering. In this work, we investigate the perf…
Rethinking multiscale cardiac electrophysiology with machine learning and predictive modelling
Chris D. Cantwell, Yumnah Mohamied, Konstantinos N. Tzortzis +6
We review some of the latest approaches to analysing cardiac electrophysiology data using machine learning and predictive modelling. Cardiac arrhythmias, particularly atrial fibril…