The paper trains a Transformer on Fourier spectral coefficients to surrogate 1D Burgers and 2D Navier-Stokes dynamics, but its claimed superiority over numerical and ML baselines is not demonstrated.
In: International Conference on Learning Representations (2023)
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The Fourier Spectral Transformer Networks For Efficient and Generalizable Nonlinear PDEs Prediction
The paper trains a Transformer on Fourier spectral coefficients to surrogate 1D Burgers and 2D Navier-Stokes dynamics, but its claimed superiority over numerical and ML baselines is not demonstrated.