Empirical scaling study finds dataset-dependent performance saturation and quantum metric trends in hybrid QNN classifiers as depth and width vary.
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Scaling Laws for Hybrid Quantum Neural Networks: Depth, Width, and Quantum-Centric Diagnostics
Empirical scaling study finds dataset-dependent performance saturation and quantum metric trends in hybrid QNN classifiers as depth and width vary.