first time I’m trying to use PINNs with Julia, as I’m reading the docs there are some parts that I’m missing.
In this example :
I see that the lines used for the predictions are:
phi = discretization.phi u_predict = reshape([first(phi([x,y],res.u)) for x in xs for y in ys],(length(xs),length(ys)))
However, in this example, the predictions are calculated like this:
phi = discretization.phi depvars = [:u,:w] minimizers_ = [res.u.depvar[depvars[i]] for i in 1:length(chain)] u_predict = [[phi[i]([t,x], minimizers_[i]) for t in ts for x in xs] for i in 1:2]
Can someone explain to me the difference between the two
u_predict lines? I’m not sure I’m following just by reading the docs.
My other question is about the
phi object, what does it contain exactly? Is it the trained network?