5 papers
Hierarchical Schedule Optimization for Fast and Robust Diffusion Model Sampling
Aihua Zhu, Rui Su, Qinglin Zhao +3
Diffusion probabilistic models have set a new standard for generative fidelity but are hindered by a slow iterative sampling process. A powerful training-free strategy to accelerat…
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…
Quantum Complex-Valued Self-Attention Model
Fu Chen, Qinglin Zhao, Li Feng +3
Self-attention has revolutionized classical machine learning, yet existing quantum self-attention models underutilize quantum states' potential due to oversimplified or incomplete…
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 Mixed-State Self-Attention Network
Fu Chen, Qinglin Zhao, Li Feng +3
Attention mechanisms have revolutionized natural language processing. Combining them with quantum computing aims to further advance this technology. This paper introduces a novel Q…