Unsupervised Generative Modeling Using Matrix Product States

• Published in: Physical review. X Vol. 8; no. 3; p. 031012
• Main Authors: Han, Zhao-Yu, Wang, Jun, Fan, Heng, Wang, Lei, Zhang, Pan
• Format: Journal Article
• Language: English
• Published: College Park American Physical Society 01.07.2018
• Subjects: 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

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...