Unsupervised Generative Modeling Using Matrix Product States

Generative 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 stat...

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Vydané v:	Physical review. X Ročník 8; číslo 3; s. 031012
Hlavní autori:	Han, Zhao-Yu, Wang, Jun, Fan, Heng, Wang, Lei, Zhang, Pan
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	College Park American Physical Society 01.07.2018
Predmet:	Algorithms Allocations Artificial intelligence Datasets Entangled states Generative adversarial networks Handwriting Machine learning Mathematical models Modelling Parameters Probability distribution Probability theory Quantum computing Quantum phenomena Quantum physics Quantum theory Representations Samples Sampling Standard data Statistical analysis Statistical methods Tensors
ISSN:	2160-3308, 2160-3308
On-line prístup:	Získať plný text
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