3 citations · 6 across the 5 of their papers we have counts for
5 papers
MediQ-GAN: Quantum-Inspired GAN for High Resolution Medical Image Generation
Qingyue Jiao, Yongcan Tang, Jun Zhuang +2
Machine learning-assisted diagnosis shows promise, yet medical imaging datasets are often scarce, imbalanced, and constrained by privacy, making data augmentation essential. Classi…
A comparison on constrain encoding methods for quantum approximate optimization algorithm
Yiwen Liu, Qingyue Jiao, Yidong Zhou +4
The Quantum Approximate Optimization Algorithm (QAOA) represents a significant opportunity for practical quantum computing applications, particularly in the era before error correc…
Graph Learning for Parameter Prediction of Quantum Approximate Optimization Algorithm
Zhiding Liang, Gang Liu, Zheyuan Liu +8
In recent years, quantum computing has emerged as a transformative force in the field of combinatorial optimization, offering novel approaches to tackling complex problems that hav…
SpacePulse: Combining Parameterized Pulses and Contextual Subspace for More Practical VQE
Zhiding Liang, Zhixin Song, Jinglei Cheng +5
In this paper, we explore the integration of parameterized quantum pulses with the contextual subspace method. The advent of parameterized quantum pulses marks a transition from tr…
RobustState: Boosting Fidelity of Quantum State Preparation via Noise-Aware Variational Training
Hanrui Wang, Yilian Liu, Pengyu Liu +10
Quantum state preparation, a crucial subroutine in quantum computing, involves generating a target quantum state from initialized qubits. Arbitrary state preparation algorithms can…