FFT preconditioning for H-Score networks concentrates predictive dependence into fewer dominant modes for stationary processes, with spectral entropy and cumulative dependence metrics predicting performance gains before training.
Principal component analysis,
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Fourier Preconditioning for Neural Feature Learning
FFT preconditioning for H-Score networks concentrates predictive dependence into fewer dominant modes for stationary processes, with spectral entropy and cumulative dependence metrics predicting performance gains before training.