Hello everyone!
I am trying to play with solving PDEs using neural networks. As I understand, this area is an example of self-supervised learning when the model (neural network itself) automatically finds its derivatives with respect to input variables, inserts them into the PDE given and then attempts to satisfy it by modifying weights.
But I encountered a problem - I can't find a way to "tell" the network how to find the derivatives. I've found NetPortGradient symbol, but there's no example showing if it can be accessed from within the network (for example, via NetGraph object).
What do you think, is it possible to construct a neural-network-based PDE solver using built-in functionality of the Wolfram Language?
