37 citations · 140 across the 14 of their papers we have counts for
11 papers · 1 filter
A Quantum-Classical Collaborative Training Architecture Based on Quantum State Fidelity
Ryan L'Abbate, Anthony D'Onofrio, Samuel Stein +5
Recent advancements have highlighted the limitations of current quantum systems, particularly the restricted number of qubits available on near-term quantum devices. This constrain…
Quantum deep recurrent reinforcement learning
Samuel Yen-Chi Chen
Recent advances in quantum computing (QC) and machine learning (ML) have drawn significant attention to the development of quantum machine learning (QML). Reinforcement learning (R…
Quantum Architecture Search via Deep Reinforcement Learning
En-Jui Kuo, Yao-Lung L. Fang, Samuel Yen-Chi Chen
Recent advances in quantum computing have drawn considerable attention to building realistic application for and using quantum computers. However, designing a suitable quantum circ…
Application of Quantum Machine Learning using the Quantum Kernel Algorithm on High Energy Physics Analysis at the LHC
Sau Lan Wu, Shaojun Sun, Wen Guan +20
Quantum machine learning could possibly become a valuable alternative to classical machine learning for applications in High Energy Physics by offering computational speed-ups. In…
Federated Quantum Machine Learning
Samuel Yen-Chi Chen, Shinjae Yoo
Distributed training across several quantum computers could significantly improve the training time and if we could share the learned model, not the data, it could potentially impr…
Quantum machine learning with differential privacy
William M Watkins, Samuel Yen-Chi Chen, Shinjae Yoo
Quantum machine learning (QML) can complement the growing trend of using learned models for a myriad of classification tasks, from image recognition to natural speech processing. A…