[WIS22] PINN: physics informed neural network to predict motion of 1D SHM

[itsshreyarora (Shrey Arora)]

Open in Wolfram Cloud ↗

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[alec (Alec Graves)]

This is absolutely amazing! I never thought to use finite difference methods inside the loss function to compute derivatives. I tried to build PINNs in WL in the past , but I gave up after realizing that WL’s neural network library based on mxnet could not automatically compute higher-order derivatives like TensorFlow or PyTorch. Your approach appears to be a promising path forward.