Shi-Ju Ran

According to our database, Shi-Ju Ran authored at least 22 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Universal scaling laws in quantum-probabilistic machine learning by tensor network towards interpreting representation and generalization powers.

Sheng-Chen Bai, Shi-Ju Ran

CoRR, 2024

Universal replication of chaotic characteristics by classical and quantum machine learning.

Sheng-Chen Bai, Shi-Ju Ran

CoRR, 2024

2023

Many-body control with reinforcement learning and tensor networks.

Ying Lu, Shi-Ju Ran

Nat. Mac. Intell., October, 2023

Tensor networks for interpretable and efficient quantum-inspired machine learning.

Shi-Ju Ran, Gang Su

CoRR, 2023

Persistent Ballistic Entanglement Spreading with Optimal Control in Quantum Spin Chains.

Ying Lu, Pei Shi, Xiao-Han Wang, Jie Hu, Shi-Ju Ran

CoRR, 2023

Compressing neural network by tensor network with exponentially fewer variational parameters.

Yong Qing, Peng-Fei Zhou, Ke Li, Shi-Ju Ran

CoRR, 2023

Intelligent diagnostic scheme for lung cancer screening with Raman spectra data by tensor network machine learning.

Yu-Jia An, Sheng-Chen Bai, Lin Cheng, Xiao-Guang Li, Cheng-en Wang, Xiao-Dong Han, Gang Su, Shi-Ju Ran, Cong Wang

CoRR, 2023

2022

Deep Machine Learning Reconstructing Lattice Topology with Strong Thermal Fluctuations.

Xiao-Han Wang, Pei Shi, Bin Xi, Jie Hu, Shi-Ju Ran

CoRR, 2022

Unsupervised Recognition of Informative Features via Tensor Network Machine Learning and Quantum Entanglement Variations.

Sheng-Chen Bai, Yi-Cheng Tang, Shi-Ju Ran

CoRR, 2022

Circuit encapsulation for efficient quantum computing based on controlled many-body dynamics.

Ying Lu, Peng-Fei Zhou, Shao-Ming Fei, Shi-Ju Ran

CoRR, 2022

2021

Entanglement-Based Feature Extraction by Tensor Network Machine Learning.

Yuhan Liu, Wen-Jun Li, Xiao Zhang, Maciej Lewenstein, Gang Su, Shi-Ju Ran

Frontiers Appl. Math. Stat., 2021

Non-parametric Active Learning and Rate Reduction in Many-body Hilbert Space with Rescaled Logarithmic Fidelity.

Wei-Ming Li, Shi-Ju Ran

CoRR, 2021

Predicting Quantum Potentials by Deep Neural Network and Metropolis Sampling.

Rui Hong, Peng-Fei Zhou, Bin Xi, Jie Hu, An-Chun Ji, Shi-Ju Ran

CoRR, 2021

Preparation of Many-body Ground States by Time Evolution with Variational Microscopic Magnetic Fields and Incomplete Interactions.

Ying Lu, Yue-Min Li, Peng-Fei Zhou, Shi-Ju Ran

CoRR, 2021

Automatically Differentiable Quantum Circuit for Many-qubit State Preparation.

Peng-Fei Zhou, Rui Hong, Shi-Ju Ran

CoRR, 2021

2020

Residual Matrix Product State for Machine Learning.

Ye-Ming Meng, Jing Zhang, Peng Zhang, Chao Gao, Shi-Ju Ran

CoRR, 2020

Deep neural network predicts parameters of quantum many-body Hamiltonians by learning visualized wave-functions.

Xinran Ma, Z. C. Tu, Shi-Ju Ran

CoRR, 2020

Tangent-Space Gradient Optimization of Tensor Network for Machine Learning.

Zheng-Zhi Sun, Shi-Ju Ran, Gang Su

CoRR, 2020

2019

Bayesian Tensor Network and Optimization Algorithm for Probabilistic Machine Learning.

Shi-Ju Ran

CoRR, 2019

Quantum Compressed Sensing with Unsupervised Tensor Network Machine Learning.

Shi-Ju Ran, Zheng-Zhi Sun, Shao-Ming Fei, Gang Su, Maciej Lewenstein

CoRR, 2019

Generative Tensor Network Classification Model for Supervised Machine Learning.

Zheng-Zhi Sun, Cheng Peng, Ding Liu, Shi-Ju Ran, Gang Su

CoRR, 2019

2018

Learning architectures based on quantum entanglement: a simple matrix product state algorithm for image recognition.

Yuhan Liu, Xiao Zhang, Maciej Lewenstein, Shi-Ju Ran

CoRR, 2018