Hello all,

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!