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Hybrid Variational Quantum Circuits for Multivariate Regression and High-Dimensional Data Reconstruction
Variational quantum circuits (VQCs) are parameterized quantum circuits optimized classically. We propose a hybrid variational quantum circuit (HVQC) extending VQCs with a classical affine post-measurement layer, enabling vector-valued regression without the linear overhead of independent scalar circuits. Theoretically, we show that elementary one-and two-qubit circuits can approximate quadratic functions and products via data re-uploading and entanglement, providing the foundations of the full architecture. Experimentally, on two synthetic image reconstruction datasets and the Friedman1 benchm
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-15T15:57:20.000Z
First collected: 2026-09-20T08:40:59.508Z. This is not the publication date.