4.4k citations · 24.2k across the 344 of their papers we have counts for
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Accelerating variational quantum algorithms with multiple quantum processors
Yuxuan Du, Yang Qian, Dacheng Tao
Variational quantum algorithms (VQAs) have the potential of utilizing near-term quantum machines to gain certain computational advantages over classical methods. Nevertheless, mode…
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…
On exploring the potential of quantum auto-encoder for learning quantum systems
Yuxuan Du, Dacheng Tao
The frequent interactions between quantum computing and machine learning revolutionize both fields. One prototypical achievement is the quantum auto-encoder (QAE), as the leading s…
Efficient measure for the expressivity of variational quantum algorithms
Yuxuan Du, Zhuozhuo Tu, Xiao Yuan +1
The superiority of variational quantum algorithms (VQAs) such as quantum neural networks (QNNs) and variational quantum eigen-solvers (VQEs) heavily depends on the expressivity of…
Towards understanding the power of quantum kernels in the NISQ era
Xinbiao Wang, Yuxuan Du, Yong Luo +1
A key problem in the field of quantum computing is understanding whether quantum machine learning (QML) models implemented on noisy intermediate-scale quantum (NISQ) machines can a…