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The increasingly photorealistic sample quality of generative image models suggests their feasibility in applications beyond image generation.
Learning multiple layers of features from tiny images, 2009
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A.B.L. Larsen, S.K. Sønderby, and O. Winther · 2015
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Deep learning face attributes in the wild
Z. Liu, P. Luo, X. Wang, and X. Tang · 2015
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Unsupervised representation learning with deep convolutional generative adversarial networks
A. Radford, L. Metz, and S. Chintala · 2015
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Imagenet large scale visual recognition challenge
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J. Zhao, M. Mathieu, R. Goroshin, and Y. Lecun · 2015
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Densely connected convolutional networks
G. Huang, Z. Liu, K.Q. Weinberger, and L. van der Maaten · 2016
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Discriminative regularization for generative models
A. Lamb, V. Dumoulin, and A. Courville · 2016
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Auxiliary deep generative models
L. Maaløe, C.K. Sønderby, S.K. Sønderby, and O. Winther · 2016
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Conditional image synthesis with auxiliary classifier gans
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Improved techniques for training gans
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Generating images with perceptual similarity metrics based on deep networks
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Adversarially learned inference
V. Dumoulin, I. Belghazi, B. Poole, A. Lamb, M. Arjovsky, O. Mastropietro, and A. Courville · 2016
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