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Quantum Fidelity Landscape-Guided Prior Calibration for Single-Circuit QGAN Image Generation
Xue Yang, Rigui Zhou, Dax Enshan Koh +5
Quantum Generative Adversarial Networks (QGANs) have emerged as representative generative models in the Noisy Intermediate-Scale Quantum (NISQ) era and have attracted increasing at…
CoQui: A Coordinate-Conditioned Quantum Implicit Generative Adversarial Network for End-to-End Image Generation
Xue Yang, Rigui Zhou, ShiZheng Jia +7
Quantum generative adversarial networks (QGANs) have attracted increasing attention for image generation using parameterized quantum circuits. Existing amplitude-based approaches f…
End-to-End QGAN-Based Image Synthesis via Neural Noise Encoding and Intensity Calibration
Xue Yang, Rigui Zhou, Shizheng Jia +5
Quantum Generative Adversarial Networks (QGANs) offer a promising path for learning data distributions on near-term quantum devices. However, existing QGANs for image synthesis avo…
iHQGAN: A Lightweight Invertible Hybrid Quantum-Classical Generative Adversarial Network for Unsupervised Image-to-Image Translation
Xue Yang, Rigui Zhou, ShiZheng Jia +6
Leveraging quantum computing's intrinsic properties to enhance machine learning has shown promise, with quantum generative adversarial networks (QGANs) demonstrating benefits in da…