A hybrid variational quantum regression design with classical geometric preconditioning and curriculum optimization improves trainability over pure quantum models while remaining behind strong classical baselines.
Power and limitations of single-qubit native quan- tum neural networks.Advances in Neural Information Processing Systems, 35:27810–27823,
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Geometric Preconditioning and Curriculum Optimization for Trainable Variational Quantum Regression
A hybrid variational quantum regression design with classical geometric preconditioning and curriculum optimization improves trainability over pure quantum models while remaining behind strong classical baselines.