4 papers
A Survey of Quantum Transformers: Architectures, Challenges and Outlooks
Hui Zhang, Qinglin Zhao, Mengchu Zhou +4
Quantum Transformers integrate the representational power of classical Transformers with the computational advantages of quantum computing. Since 2022, research in this area has ra…
Overcoming Dimensional Factorization Limits in Discrete Diffusion Models through Quantum Joint Distribution Learning
Chuangtao Chen, Qinglin Zhao, MengChu Zhou +3
Discrete diffusion models represent a significant advance in generative modeling, demonstrating remarkable success in synthesizing complex, high-quality discrete data. However, to…
HQViT: Hybrid Quantum Vision Transformer for Image Classification
Hui Zhang, Qinglin Zhao, Mengchu Zhou +1
Transformer-based architectures have revolutionized the landscape of deep learning. In computer vision domain, Vision Transformer demonstrates remarkable performance on par with or…
Quantum Generative Diffusion Model: A Fully Quantum-Mechanical Model for Generating Quantum State Ensemble
Chuangtao Chen, Qinglin Zhao, MengChu Zhou +3
Mixed quantum states are the native description of many physically important quantum systems, making their generation a fundamental task in quantum information processing. However,…