• Corpus ID: 252567996

Towards a scalable discrete quantum generative adversarial neural network

  title={Towards a scalable discrete quantum generative adversarial neural network},
  author={Smit Chaudhary and Patrick Huembeli and Ian MacCormack and Taylor Lee Patti and Jean Kossaifi and Alexey Galda},
We introduce a fully quantum generative adversarial network intended for use with binary data. The architecture incorporates several features found in other classical and quantum machine learning models, which up to this point had not been used in conjunction. In particular, we incorporate noise reuploading in the generator, auxiliary qubits in the discriminator to enhance expressivity, and a direct connection between the generator and discriminator circuits, obviating the need to access the… 



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Back-propagation repeatedly adjusts the weights of the connections in the network so as to minimize a measure of the difference between the actual output vector of the net and the desired output vector, which helps to represent important features of the task domain.

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Supervised Learning with Quantum Computers

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    npj Quantum Information 5

    • 1
    • 2019