We recently proposed a method that uses distance fields to exactly impose boundary conditions in physics-informed neural networks (PINN). This contribution is available as an arXiv preprint.
We recently proposed a method that uses distance fields to exactly impose boundary conditions in physics-informed neural networks (PINN). This contribution is available as an arXiv preprint.
Nice work, but I think an
Nice work, but I think an important and very similar work is left out: https://arxiv.org/abs/2006.08472
In reply to Nice work, but I think an by haghighat
Seems the link is not
Seems the link is not correctly reflected:
Rao C, Sun H, Liu Y. Physics informed deep learning for computational elastodynamics without labeled data. arXiv preprint arXiv:2006.08472. 2020 Jun 10.