Is it possible to modify the loss function in PINNs? like instead of loss function of variables, may I modify it to loss of sin or cos of variables?

See the `additional_loss`

function. Unless you mean something different?

I saw that the `additional_loss`

function just have the syntax that `additional_loss(phi, θ, p)`

. The problem’s variables include the phase angle, and there are the functions of sin and cos of them. If I use `additional_loss(phi, θ, p)`

the network could estimate the loss by sin or cos of phase angle or do I need to implement the specific function at the argument of `additional_loss`

?

The tutorial has the information for the adaptive loss function, so there are any functions for `additional_loss`

or do I need to define the new function for `additional_loss`

?

You just define a new function. It can be any differentiable Julia function.