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Intro
What are Neural Operators?
About FNOs and their multiscale property
About Spectral Convolutions
A "Fourier Layer"
Stacking Layers with Lifting & Projection
Our Example: Solving the 1d Burgers equation
Minor technicalities
Installing and Importing packages
Obtaining the dataset and reading it in
Plot and Discussion of the dataset
Prepare training & test data
Implementing Spectral Convolution
Implementing a Fourier Layer/Block
Implementing the full FNO
A simple dataloader in JAX
Loss Function & Training Loop
Visualize loss history
Test prediction with trained FNO
Zero-Shot superresolution
Compute error as reported in FNO paper
Summary
Outro