A machine learning minimal residual method for solving quantities of interest of parametric PDEs
Ignacio Brevis, Ignacio Muga, David Pardo, Oscar Rodríguez and Kristoffer G. van der Zee
Using Graph Neural Network for gas-liquid interface reconstruction in Volume Of Fluid methods
Michele-Alessandro BUCCI, Jean-Marc GRATIEN, Thibault FANEY, Tamon NAKANO and Guillaume CHARPIAT
Long-time prediction of nonlinear parametrized dynamical systems by deep learning-based reduced order models
Federico Fatone, Stefania Fresca and Andrea Manzoni
Parameter estimation for differential problems through multi-fidelity physics-informed neural networks
Francesco Regazzoni, Stefano Pagani, Alessandro Cosenza, Alessandro Lombardi and Alfio Quarteroni
A collocation method based on single-layer feedforward neural network for the resolution of Elliptic PDEs
Francesco Calabrò
A PINN computational study for a scalar 2D inviscid Burgers model with Riemann data
Rafael Carniello, João Florindo and Eduardo Abreu
A novel Machine Learning method for accurate and real-time numerical simulations of cardiac electromechanics
Luca Dede‘, Francesco Regazzoni, Matteo Salvador and Alfio Quarteroni
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