[R] Can one Train Parameterized-geometry PINNs without data?

Hello everybody,

i have been learning about Physics informed neural networks and how the automatic differentiation allows us to compute the Physics residuals and thereby learn the process. So from my understanding, it seems that if one has the physical governing equations ready and the boundary conditions also set properly, a neural network should theoretically be able to learn the physics without any previous data (simulation, FEM etc). There are some papers who learn this but all typically constrain to …

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