8 citations · 13 across the 3 of their papers we have counts for
5 papers
Efficient and practical quantum compiler towards multi-qubit systems with deep reinforcement learning
Qiuhao Chen, Yuxuan Du, Qi Zhao +3
Efficient quantum compiling tactics greatly enhance the capability of quantum computers to execute complicated quantum algorithms. Due to its fundamental importance, a plethora of…
Quantum circuit architecture search on a superconducting processor
Kehuan Linghu, Yang Qian, Ruixia Wang +14
Variational quantum algorithms (VQAs) have shown strong evidences to gain provable computational advantages for diverse fields such as finance, machine learning, and chemistry. How…
The dilemma of quantum neural networks
Yang Qian, Xinbiao Wang, Yuxuan Du +2
The core of quantum machine learning is to devise quantum models with good trainability and low generalization error bound than their classical counterparts to ensure better reliab…
QFlow lite dataset: A machine-learning approach to the charge states in quantum dot experiments
Justyna P. Zwolak, Sandesh S. Kalantre, Xingyao Wu +2
Over the past decade, machine learning techniques have revolutionized how research is done, from designing new materials and predicting their properties to assisting drug discovery…
Multiparty quantum data hiding with enhanced security and remote deletion
Xingyao Wu, Jianxin Chen
One of the applications of quantum technology is to use quantum states and measurements to communicate which offers more reliable security promises. Quantum data hiding, which give…