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  <title><![CDATA[A hybrid quantum enabled RBM advantage: convolutional autoencoders for quantum image compression and generative learning]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/927/A-hybrid-quantum-enabled-RBM-advantage-convolutional-autoencoders-for-quantum-image-compression-and-generative-learning</link>
  <description><![CDATA[Understanding how the D-Wave quantum computer could be used for machine learning problems is of growing interest. Our work explores the feasibility of using the D-Wave as a sampler for a machine learning task. We describe a hybrid method that combines a classical deep neural network autoencoder with a quantum annealing Restricted Boltzmann Machine (RBM) using the D-Wave for image generation. Our method overcomes two key limitations in the 2000-qubit D-Wave processor, namely the limited number...]]></description>
  <dc:date>2020-05-20</dc:date>
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