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Hybrid Variational Quantum Circuits for Multivariate Regression and High-Dimensional Data Reconstruction

Paper recorded by Signals 4 on 2026-09-15 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-15 on arXiv · recorded by Signals 4 on 2026-09-16

Category: cs.LG · 机器学习 · first seen 2026-09-16

Abstract

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 fu

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#35 most recent of 215 cs.LG papers we have recorded · ↑ newer: Large Language Models Develop Belief State Geometry In-Context · ↓ older: Type-IV Code Clone Detection via Layer-Wise Non-Contrastive Representa
Cite this page: Hybrid Variational Quantum Circuits for Multivariate Regression and High-Dimensional Data Reconstruction: the #35 most recent of 215 cs.LG papers we have recorded (as of 2026-09-15). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/hybrid-variational-quantum-circuits-for-multivariate-regression-and-high-dimensi.html
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