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If you have 2 or more functions as Neural nets, say f and g.
And they are coupled by a differential equation.
If we already idea how f should look like say we have a mock function f_m for f
I would like to:
Train f to f_m.
Solve/optimize the PDE for g, without updating f.
Then solve/optimize the PDE for f, without updating g.
We need at way to tell the optimizer to not optimize on some functions.
The text was updated successfully, but these errors were encountered:
If you have 2 or more functions as Neural nets, say f and g.
And they are coupled by a differential equation.
If we already idea how f should look like say we have a mock function f_m for f
I would like to:
We need at way to tell the optimizer to not optimize on some functions.
The text was updated successfully, but these errors were encountered: