S. L. Juárez-Osorio

Empirical Characterization of Learning Geometry in Hybrid Quantum Forecasting Models

The study identifies architecture-dependent learning behavior that is masked by endpoint accuracy alone, and demonstrates that comparable generalization can emerge from substantially different learning trajectories and that individual NTK diagnostics do not provide monotonic predictors of validation convergence.