Tensor Networks for Interpretable and Efficient Quantum-Inspired Machine Learning by Shi-Ju Ran, Gang Su

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Non-Parametric Semi-Supervised Learning in Many-Body Hilbert Space with Rescaled Logarithmic Fidelity by Wei-Ming Li, Shi-Ju Ran

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Editorial: Tensor network approaches for quantum many-body physics and machine learning by Shi-Ju Ran, Qibin Zhao, Peng Zhang, Chu Guo

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Quantum compiling with a variational instruction set for accurate and fast quantum computing by Ying Lu, Peng-Fei Zhou, Shao-Ming Fei, Shi-Ju Ran

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Residual matrix product state for machine learning by Ye-Ming Meng, Jing Zhang, Peng Zhang, Chao Gao, Shi-Ju Ran

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Tensor network compressed sensing with unsupervised machine learning by Shi-Ju Ran, Zheng-Zhi Sun, Shao-Ming Fei, Gang Su, Maciej Lewenstein

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Predicting quantum potentials by deep neural network and metropolis sampling by Rui Hong, Peng-Fei Zhou, Bin Xi, Jie Hu, An-Chun Ji, Shi-Ju Ran

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Machine learning by unitary tensor network of hierarchical tree structure by Ding Liu, Shi-Ju Ran, Peter Wittek, Cheng Peng, Raul Blázquez García, Gang Su, Maciej Lewenstein

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