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Amplitude modifiers can ensure Lipschitz continuity in neural networks, enabling robust audio signal recovery with guaranteed convergence.
Explicitly modeling the dependency between amplitude and phase allows PolarBM to significantly outperform traditional models in audio signal accuracy.
