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View Code? Open in Web Editor NEWAn extension of Fourier Neural Operator to finite-dimensional input and/or output spaces.
Home Page: https://doi.org/10.22002/r5ga1-55d06
License: MIT License
An extension of Fourier Neural Operator to finite-dimensional input and/or output spaces.
Home Page: https://doi.org/10.22002/r5ga1-55d06
License: MIT License
^^ The nonlinear processing at the beginning of all the architectures in vec_to_*.py files may not be necessary and hurt accuracy. We should try removing this nonlinearity to see if that helps.
FNF (Fourier neural functional) could also be named Fourier Neural Encoder (FNE) for consistency with FND. Then Fourier Neural Network (FNN) function could be renamed Fourier Neural Function (FNF).
Can decide later.
fourier-neural-mappings
change readme to reflect this
also add conda yml environment requirement following the readme template here
acknowledgements in repo (original fno code, pyapprox, etc)
Add argument to choose whether to use 1D or 2D spatial layers in the latent function space.
Change repo name and classes to "Functionals" instead of "Functional"?
na
Does the truncation of information in Fourier Neural Functionals cause issues? It takes a function and integrates it against another function with k_max Fourier modes (so only the first k_maxd Fourier modes are used). But unlike FNO layers, there is no notion of skip connection to retain the truncated modes i.e. use all the information in the input.
An alternative could be to take function
So we would have
torch.cat(Lu, \int MLP(u(x)) dx),
where L is the FNF map.
FNO2d
FNO2dto3d
FNF2d
Cleanup repo before making public: models
directory, shared.py
for shared layers and fucntions, etc.
After clean PR #7 , scripts have not been tested so there are perhaps some errors in the function import paths. Need to check all.
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