Hey everyone,
I am testing NeuralPDE to simulate hydrodynamic shocks and I would like to try the residual/gradient adaptative sampling of data, as described in the article in the following link : Physics-informed neural networks with residual/gradient-based adaptive sampling methods for solving partial differential equations with sharp solutions | Applied Mathematics and Mechanics.
Is it possible to do this with the current version of NeuralPDE, or to adapt it to make it work?
Thank you for your answers!