RBM Image Generation Using the D-Wave 2000Q

Jennifer Sleeman, Milton Halem, John E. Dorband

Published Oct 30, 2019• 0 citations

Abstract

We describe a hybrid approach that combines a deep convolutional neural network autoencoder and a quantum Restricted Boltzmann Machine (RBM) for image generation using the D-Wave 2000Q. We compare the quantum learned distribution with the classical learned distribution, and quantify the quantum effects on latent representations.

DOI: 10.13016/m2zspl-zhvf

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