27 citations · 29 across the 5 of their papers we have counts for
5 papers
A Hamiltonian-Inspired Local-Operator Ansatz for Slimming Large Language Models
Ying Lu, Peng-Fei Zhou, Qi-Xuan Fang +3
Dense linear maps carry much of the parameter and computational burden of modern neural networks, yet their dense form leaves the organization of learned couplings implicit. Quantu…
Matrix-product entanglement characterizing the optimality of state-preparation quantum circuits
Shuo Qi, Wen-Jun Li, Gang Su +1
Multipartite entanglement offers a powerful framework for understanding the complex collective phenomena in quantum many-body systems that are often beyond the description of conve…
Efficient Quantum Mixed-State Tomography with Unsupervised Tensor Network Machine Learning
Wen-jun Li, Kai Xu, Heng Fan +2
Quantum state tomography (QST) is plagued by the ``curse of dimensionality'' due to the exponentially-scaled complexity in measurement and data post-processing. Efficient QST schem…
Intelligent diagnostic scheme for lung cancer screening with Raman spectra data by tensor network machine learning
Yu-Jia An, Sheng-Chen Bai, Lin Cheng +6
Artificial intelligence (AI) has brought tremendous impacts on biomedical sciences from academic researches to clinical applications, such as in biomarkers' detection and diagnosis…
Entanglement-guided architectures of machine learning by quantum tensor network
Yuhan Liu, Xiao Zhang, Maciej Lewenstein +1
It is a fundamental, but still elusive question whether the schemes based on quantum mechanics, in particular on quantum entanglement, can be used for classical information process…