176 citations · 1.4k across the 70 of their papers we have counts for
5 papers · 1 filter
Deep Machine Learning Reconstructing Lattice Topology with Strong Thermal Fluctuations
Xiao-Han Wang, Pei Shi, Bin Xi +2
Applying artificial intelligence to scientific problems (namely AI for science) is currently under hot debate. However, the scientific problems differ much from the conventional on…
Bayesian Tensor Network with Polynomial Complexity for Probabilistic Machine Learning
Shi-Ju Ran
It is known that describing or calculating the conditional probabilities of multiple events is exponentially expensive. In this work, Bayesian tensor network (BTN) is proposed to e…
Quantum Compressed Sensing with Unsupervised Tensor-Network Machine Learning
Shi-Ju Ran, Zheng-Zhi Sun, Shao-Ming Fei +2
We propose tensor-network compressed sensing (TNCS) by combining the ideas of compressed sensing, tensor network (TN), and machine learning, which permits novel and efficient quant…
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…
Machine Learning by Unitary Tensor Network of Hierarchical Tree Structure
Ding Liu, Shi-Ju Ran, Peter Wittek +4
The resemblance between the methods used in quantum-many body physics and in machine learning has drawn considerable attention. In particular, tensor networks (TNs) and deep learni…