4 papers · 1 filter
On the Design of Expressive and Trainable Pulse-based Quantum Machine Learning Models
Han-Xiao Tao, Xin Wang, Re-Bing Wu
Pulse-based Quantum Machine Learning (QML) has emerged as a novel paradigm in quantum artificial intelligence due to its exceptional hardware efficiency. For practical applications…
Predictive Performance of Deep Quantum Data Re-uploading Models
Xin Wang, Han-Xiao Tao, Re-Bing Wu
Quantum machine learning models incorporating data re-uploading circuits have garnered significant attention due to their exceptional expressivity and trainability. However, their…
On the Role of Controllability in Pulse-based Quantum Machine Learning Models
Han-Xiao Tao, Re-Bing Wu
Pulse-based quantum machine learning (QML) models possess full expressivity when they are ensemble controllable. However, it has also been shown that barren plateaus emerge in such…
Unleashing the Expressive Power of Pulse-Based Quantum Neural Networks
Han-Xiao Tao, Jiaqi Hu, Re-Bing Wu
Quantum machine learning (QML) based on Noisy Intermediate-Scale Quantum (NISQ) devices hinges on the optimal utilization of limited quantum resources. While gate-based QML models…