Author

U. Parampalli

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Jul 2026

Quantum Spectral Model: Data Reuploading with Input-Conditioned Frequency Support

New light is shed on quantum machine-learning model design by showing how input-conditioned spectral representations can provide an analysable inductive bias, while offering a broader perspective on structure-aware model design in machine learning and artificial intelligence.

Pei-Yong Wang, Parampalli Udaya, Casey R. Myers · arXiv.org · 0 citations

Preprint Jul 2026

When cheap gradients fail: the measurement cost of attacking quantum classifiers

It is shown that finite quantum measurement statistics (shot noise) act as a built-in defense against gradient-based test-time attacks whose cost scales unfavorably for the attacker.

Bacui Li, Chandra Thapa, Tansu Alpcan et al. · 0 citations