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math.NA2023★ 31 cited
Enhancing training of physics-informed neural networks using domain-decomposition based preconditioning strategies
Alena Kopaničáková, Hardik Kothari, George Em Karniadakis +1
We propose to enhance the training of physics-informed neural networks (PINNs). To this aim, we introduce nonlinear additive and multiplicative preconditioning strategies for the w…
math.NA2023★ 17 cited
Boundary Integral Formulation of the Cell-by-Cell Model of Cardiac Electrophysiology
Giacomo Rosilho de Souza, Rolf Krause, Simone Pezzuto
We propose a boundary element method for the accurate solution of the cell-by-cell bidomain model of electrophysiology. The cell-by-cell model, also called Extracellular-Membrane-I…