Poster Presentation Presented at the 2019 Rising Stars in EECS Workshop

RBM Image Generation Using the D-Wave 2000Q

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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.


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