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Is the shift_scal_points() way important in the def get_fourier_emebddings(xyz, num_channles, input_range)?
My model uses your version of get_fourier_emebddings(), but the performance is similar to the MLP way. The only difference is that I have not used the sshift_scal_points() because my input has been normalized before being fed to get_fourier_emebddings().
Do you have any suggestions about that? Learning rate or some other things would affect the application of Fourier features?
I appreciate it.
The text was updated successfully, but these errors were encountered:
Hi, thank you for your excellent work.
Is the shift_scal_points() way important in the def get_fourier_emebddings(xyz, num_channles, input_range)?
My model uses your version of get_fourier_emebddings(), but the performance is similar to the MLP way. The only difference is that I have not used the sshift_scal_points() because my input has been normalized before being fed to get_fourier_emebddings().
Do you have any suggestions about that? Learning rate or some other things would affect the application of Fourier features?
I appreciate it.
The text was updated successfully, but these errors were encountered: