ITP OpenIR  > SCI期刊论文
Han, ZY; Wang, J; Fan, H1,3; Wang, L1,3; Zhang, P2
Unsupervised Generative Modeling Using Matrix Product States
Source PublicationPHYSICAL REVIEW X
Language英语
KeywordNEURAL-NETWORKS RENORMALIZATION-GROUP BOLTZMANN MACHINES TENSOR NETWORKS ALGORITHM SYSTEMS
AbstractGenerative modeling, which learns joint probability distribution from data and generates samples according to it, is an important task in machine learning and artificial intelligence. Inspired by probabilistic interpretation of quantum physics, we propose a generative model using matrix product states, which is a tensor network originally proposed for describing (particularly one-dimensional) entangled quantum states. Our model enjoys efficient learning analogous to the density matrix renormalization group method, which allows dynamically adjusting dimensions of the tensors and offers an efficient direct sampling approach for generative tasks. We apply our method to generative modeling of several standard data sets including the Bars and Stripes random binary patterns and the MNIST handwritten digits to illustrate the abilities, features, and drawbacks of our model over popular generative models such as the Hopfield model, Boltzmann machines, and generative adversarial networks. Our work sheds light on many interesting directions of future exploration in the development of quantum-inspired algorithms for unsupervised machine learning, which are promisingly possible to realize on quantum devices.
2018
ISSN2160-3308
Volume8Issue:3Pages:31012
Subject AreaPhysics
MOST Discipline CataloguePhysics, Multidisciplinary
DOI10.1103/PhysRevX.8.031012
Indexed BySCIE
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Cited Times:19[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.itp.ac.cn/handle/311006/22862
CollectionSCI期刊论文
计算平台成果
Affiliation1.Peking Univ, Sch Phys, Beijing 100871, Peoples R China
2.Chinese Acad Sci, Inst Phys, Beijing 100190, Peoples R China
3.Chinese Acad Sci, Inst Theoret Phys, Key Lab Theoret Phys, Beijing 100190, Peoples R China
4.Univ Chinese Acad Sci, CAS Ctr Excellence Topol Quantum Computat, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Han, ZY,Wang, J,Fan, H,et al. Unsupervised Generative Modeling Using Matrix Product States[J]. PHYSICAL REVIEW X,2018,8(3):31012.
APA Han, ZY,Wang, J,Fan, H,Wang, L,&Zhang, P.(2018).Unsupervised Generative Modeling Using Matrix Product States.PHYSICAL REVIEW X,8(3),31012.
MLA Han, ZY,et al."Unsupervised Generative Modeling Using Matrix Product States".PHYSICAL REVIEW X 8.3(2018):31012.
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