Neural networks prioritize amplitude over phase in Fourier space during training on translation-invariant data; power-law spectra accelerate phase learning despite not aiding classification.
& Ginis, V.Linear CNNs discover the statistical structure of the dataset using only the most dominant frequenciesinInternational Conference on Machine Learning(2023), 27876–27906
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A Fourier perspective on the learning dynamics of neural networks: from sample complexities to mechanistic insights
Neural networks prioritize amplitude over phase in Fourier space during training on translation-invariant data; power-law spectra accelerate phase learning despite not aiding classification.