Quantum latent distributions from boson samplers are shown in theory to expand the output distribution class of invertible Lipschitz generators, and in GAN benchmarks on QM9 to beat Gaussian, Bernoulli, and distinguishable-photon baselines, though the gain is hyperparameter-sensitive.
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Quantum latent distributions in deep generative models
Quantum latent distributions from boson samplers are shown in theory to expand the output distribution class of invertible Lipschitz generators, and in GAN benchmarks on QM9 to beat Gaussian, Bernoulli, and distinguishable-photon baselines, though the gain is hyperparameter-sensitive.