I am trying to solve an inverse problem with NeuralPDE as presented in the documentation here.
I am wondering if it was possible to define a sampling strategy to evaluate the pde_loss of the NeuralPDE.PhysicsInformedNN interface at the same points as the one used in the additional_loss?
(u_ , t_) = ground_truth_data depvars = [:x,:y,:z] function additional_loss(phi, θ , p) return sum(sum(abs2, phi[i](t_ , θ[depvars[i]]) .- u_[[i], :])/len for i in 1:1:3) end discretization = NeuralPDE.PhysicsInformedNN([chain1 , chain2, chain3],stratedy=NeuralPDE.GridTraining(dt), param_estim=true, additional_loss=additional_loss)
In other words, is it possible to evaluate the pde_loss only on the points where we have ground truth data?
Thanks in advance!