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Recent years have seen adversarial losses been applied to many fields.
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Deep sparse rectifier neural networks
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Generative adversarial nets
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Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E. Hinton · 2016
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f-GAN: Training generative neural samplers using variational divergence minimization
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Unsupervised representation learning with deep convolutional generative adversarial networks
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Improved techniques for training GANs
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GANs trained by a two time-scale update rule converge to a local Nash equilibrium
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Many paths to equilibrium: GANs do not need to decrease a divergence at every step
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Spectral normalization for generative adversarial networks
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Fisher GAN
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