75 citations · 219 across the 10 of their papers we have counts for
Showing 2022Show all
2 papers · 1 filter
math.NA2022★ 67 cited
Enforcing Dirichlet boundary conditions in physics-informed neural networks and variational physics-informed neural networks
S. Berrone, C. Canuto, M. Pintore +1
In this paper, we present and compare four methods to enforce Dirichlet boundary conditions in Physics-Informed Neural Networks (PINNs) and Variational Physics-Informed Neural Netw…
math.NA2022★ 29 cited
Solving PDEs by Variational Physics-Informed Neural Networks: an a posteriori error analysis
Stefano Berrone, Claudio Canuto, Moreno Pintore
We consider the discretization of elliptic boundary-value problems by variational physics-informed neural networks (VPINNs), in which test functions are continuous, piecewise linea…