Harmonics of Learning: A Mathematical Theory for the Rise of Fourier Features in Learning Systems Like Neural Networks

Artificial neural networks (ANNs) show a remarkable pattern when trained on natural data irrespective of exact initialization, dataset, or training objective; models trained on the same data domain converge to similar learned patterns. For example, for different image models, the initial layer weights tend to converge to Gabor filters and color-contrast detectors. Many such features […]

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