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Comparing the Effects of Boltzmann Machines as Associative Memory in Generative Adversarial Networks between Classical and Quantum Samplings
We investigate the quantum effect on machine learning (ML) models exemplified by the Generative Adversarial Network (GAN), which is a promising deep learning framework. In the general GAN framework, the generator maps uniform noise to a fake image. In this study, we utilize the Associative Adversarial Network (AAN), which consists …