Next Article in Journal
Multi-Type Node Detection in Network Communities
Previous Article in Journal
A Quantum Cellular Automata Type Architecture with Quantum Teleportation for Quantum Computing
Open AccessArticle

Probabilistic Modeling with Matrix Product States

by 1,* and 2
1
Flatiron Institute, New York, NY 10010, USA
2
Tunnel, New York, NY 10001, USA
*
Author to whom correspondence should be addressed.
Entropy 2019, 21(12), 1236; https://doi.org/10.3390/e21121236
Received: 13 November 2019 / Revised: 10 December 2019 / Accepted: 12 December 2019 / Published: 17 December 2019
(This article belongs to the Section Quantum Information)
Inspired by the possibility that generative models based on quantum circuits can provide a useful inductive bias for sequence modeling tasks, we propose an efficient training algorithm for a subset of classically simulable quantum circuit models. The gradient-free algorithm, presented as a sequence of exactly solvable effective models, is a modification of the density matrix renormalization group procedure adapted for learning a probability distribution. The conclusion that circuit-based models offer a useful inductive bias for classical datasets is supported by experimental results on the parity learning problem. View Full-Text
Keywords: machine learning; density matrix renormalization group; quantum information machine learning; density matrix renormalization group; quantum information
Show Figures

Figure 1

MDPI and ACS Style

Stokes, J.; Terilla, J. Probabilistic Modeling with Matrix Product States. Entropy 2019, 21, 1236. https://doi.org/10.3390/e21121236

AMA Style

Stokes J, Terilla J. Probabilistic Modeling with Matrix Product States. Entropy. 2019; 21(12):1236. https://doi.org/10.3390/e21121236

Chicago/Turabian Style

Stokes, James; Terilla, John. 2019. "Probabilistic Modeling with Matrix Product States" Entropy 21, no. 12: 1236. https://doi.org/10.3390/e21121236

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop