22 citations · 69 across the 11 of their papers we have counts for
17 papers
Shuffle-QUDIO: accelerate distributed VQE with trainability enhancement and measurement reduction
Yang Qian, Yuxuan Du, Dacheng Tao
The variational quantum eigensolver (VQE) is a leading strategy that exploits noisy intermediate-scale quantum (NISQ) machines to tackle chemical problems outperforming classical a…
QAOA-in-QAOA: solving large-scale MaxCut problems on small quantum machines
Zeqiao Zhou, Yuxuan Du, Xinmei Tian +1
The design of fast algorithms for combinatorial optimization greatly contributes to a plethora of domains such as logistics, finance, and chemistry. Quantum approximate optimizatio…
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…
Unentangled quantum reinforcement learning agents in the OpenAI Gym
Jen-Yueh Hsiao, Yuxuan Du, Wei-Yin Chiang +2
Classical reinforcement learning (RL) has generated excellent results in different regions; however, its sample inefficiency remains a critical issue. In this paper, we provide con…
DyRep: Bootstrapping Training with Dynamic Re-parameterization
Tao Huang, Shan You, Bohan Zhang +4
Structural re-parameterization (Rep) methods achieve noticeable improvements on simple VGG-style networks. Despite the prevalence, current Rep methods simply re-parameterize all op…
Efficient Bipartite Entanglement Detection Scheme with a Quantum Adversarial Solver
Xu-Fei Yin, Yuxuan Du, Yue-Yang Fei +10
The recognition of entanglement states is a notoriously difficult problem when no prior information is available. Here, we propose an efficient quantum adversarial bipartite entang…