Shi-Ju Ran

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 21

Top Topics

Quantum Computing

Machine Learning

Top Venues

Nat. Mac. Intell.

Frontiers Appl. Math. Stat.

Publications

Sheng-Chen Bai, Shi-Ju Ran
Universal replication of chaotic characteristics by classical and quantum machine learning. CoRR (2024)
Shi-Ju Ran, Gang Su
Tensor networks for interpretable and efficient quantum-inspired machine learning. CoRR (2023)
Yong Qing, Peng-Fei Zhou, Ke Li, Shi-Ju Ran
Compressing neural network by tensor network with exponentially fewer variational parameters. CoRR (2023)
Ying Lu, Pei Shi, Xiao-Han Wang, Jie Hu, Shi-Ju Ran
Persistent Ballistic Entanglement Spreading with Optimal Control in Quantum Spin Chains. CoRR (2023)
Ying Lu, Shi-Ju Ran
Many-body control with reinforcement learning and tensor networks. Nat. Mac. Intell. 5 (10) (2023)
Yu-Jia An, Sheng-Chen Bai, Lin Cheng, Xiao-Guang Li, Cheng-en Wang, Xiao-Dong Han, Gang Su, Shi-Ju Ran, Cong Wang
Intelligent diagnostic scheme for lung cancer screening with Raman spectra data by tensor network machine learning. CoRR (2023)
Ying Lu, Peng-Fei Zhou, Shao-Ming Fei, Shi-Ju Ran
Circuit encapsulation for efficient quantum computing based on controlled many-body dynamics. CoRR (2022)
Sheng-Chen Bai, Yi-Cheng Tang, Shi-Ju Ran
Unsupervised Recognition of Informative Features via Tensor Network Machine Learning and Quantum Entanglement Variations. CoRR (2022)
Xiao-Han Wang, Pei Shi, Bin Xi, Jie Hu, Shi-Ju Ran
Deep Machine Learning Reconstructing Lattice Topology with Strong Thermal Fluctuations. CoRR (2022)
Peng-Fei Zhou, Rui Hong, Shi-Ju Ran
Automatically Differentiable Quantum Circuit for Many-qubit State Preparation. CoRR (2021)
Yuhan Liu, Wen-Jun Li, Xiao Zhang, Maciej Lewenstein, Gang Su, Shi-Ju Ran
Entanglement-Based Feature Extraction by Tensor Network Machine Learning. Frontiers Appl. Math. Stat. 7 (2021)
Wei-Ming Li, Shi-Ju Ran
Non-parametric Active Learning and Rate Reduction in Many-body Hilbert Space with Rescaled Logarithmic Fidelity. CoRR (2021)
Rui Hong, Peng-Fei Zhou, Bin Xi, Jie Hu, An-Chun Ji, Shi-Ju Ran
Predicting Quantum Potentials by Deep Neural Network and Metropolis Sampling. CoRR (2021)
Ying Lu, Yue-Min Li, Peng-Fei Zhou, Shi-Ju Ran
Preparation of Many-body Ground States by Time Evolution with Variational Microscopic Magnetic Fields and Incomplete Interactions. CoRR (2021)
Xinran Ma, Z. C. Tu, Shi-Ju Ran
Deep neural network predicts parameters of quantum many-body Hamiltonians by learning visualized wave-functions. CoRR (2020)
Zheng-Zhi Sun, Shi-Ju Ran, Gang Su
Tangent-Space Gradient Optimization of Tensor Network for Machine Learning. CoRR (2020)
Ye-Ming Meng, Jing Zhang, Peng Zhang, Chao Gao, Shi-Ju Ran
Residual Matrix Product State for Machine Learning. CoRR (2020)
Zheng-Zhi Sun, Cheng Peng, Ding Liu, Shi-Ju Ran, Gang Su
Generative Tensor Network Classification Model for Supervised Machine Learning. CoRR (2019)
Shi-Ju Ran
Bayesian Tensor Network and Optimization Algorithm for Probabilistic Machine Learning. CoRR (2019)
Shi-Ju Ran, Zheng-Zhi Sun, Shao-Ming Fei, Gang Su, Maciej Lewenstein
Quantum Compressed Sensing with Unsupervised Tensor Network Machine Learning. CoRR (2019)
Yuhan Liu, Xiao Zhang, Maciej Lewenstein, Shi-Ju Ran
Learning architectures based on quantum entanglement: a simple matrix product state algorithm for image recognition. CoRR (2018)