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We train a generator by maximum likelihood and we also train the same generator architecture by Wasserstein GAN.
Gradient-based learning applied to document recognition
LeCun, Yann, Bottou, Léon, Bengio, Yoshua, and Haffner, Patrick · 1998
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Auto-encoding variational Bayes
Kingma, Diederik P and Welling, Max · 2013
Earlier work this paper cites.
Generative adversarial nets
Goodfellow, Ian, Pouget-Abadie, Jean, Mirza, Mehdi, Xu, Bing, Warde-Farley, David, Ozair, Sherjil, Courville, Aaron, and Bengio, Yoshua · 2014
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Stochastic backpropagation and approximate inference in deep generative models
Rezende, Danilo Jimenez, Mohamed, Shakir, and Wierstra, Daan · 2014
Earlier work this paper cites.
Deep learning face attributes in the wild
Liu, Ziwei, Luo, Ping, Wang, Xiaogang, and Tang, Xiaoou · 2015
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Unsupervised representation learning with deep convolutional generative adversarial networks
Radford, Alec, Metz, Luke, and Chintala, Soumith · 2015
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A note on the evaluation of generative models
Theis, Lucas, Oord, Aäron van den, and Bethge, Matthias · 2015
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Density estimation using real NVP
Dinh, Laurent, Sohl-Dickstein, Jascha, and Bengio, Samy · 2016
Cited alongside, same era.
Towards conceptual compression
Gregor, Karol, Besse, Frederic, Rezende, Danilo Jimenez, Danihelka, Ivo, and Wierstra, Daan · 2016
Cited alongside, same era.
Kernel mean embedding of distributions: A review and beyonds
Muandet, Krikamol, Fukumizu, Kenji, Sriperumbudur, Bharath, and Schölkopf, Bernhard · 2016
Cited alongside, same era.
Conditional image generation with PixelCNN decoders
Oord, Aaron van den, Kalchbrenner, Nal, Vinyals, Oriol, Espeholt, Lasse, Graves, Alex, and Kavukcuoglu, Koray · 2016
Cited alongside, same era.
On the quantitative analysis of decoder-based generative models
Wu, Yuhuai, Burda, Yuri, Salakhutdinov, Ruslan, and Grosse, Roger · 2016
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Towards Principled Methods for Training Generative Adversarial Networks
Arjovsky, M. and Bottou, L · 2017
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Arjovsky, Martin, Chintala, Soumith, and Bottou, Léon · 2017
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Improved training of wasserstein gans
Gulrajani, Ishaan, Ahmed, Faruk, Arjovsky, Martin, Dumoulin, Vincent, and Courville, Aaron · 2017
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Variational inference using implicit models, part I: Bayesian logistic regression
Huszár, Ferenc · 2017
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Santoro, Adam, Bartunov, Sergey, Botvinick, Matthew, Wierstra, Daan, and Lillicrap, Timothy · 2016
Cited alongside, same era.
Matching networks for one shot learning
Vinyals, Oriol, Blundell, Charles, Lillicrap, Tim, Wierstra, Daan, et al · 2016
Cited alongside, same era.
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Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks
Mescheder, L., Nowozin, S., and Geiger, A · 2017
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