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Generative Adversarial Networks (GAN) (Goodfellow et al., 2014) are an effective method for training generative models of complex data such as natural images.
Maximum likelihood from incomplete data via the EM algorithm
A. P. Dempster, N. M. Laird, and D. B. Rubin · 1977
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A decision-theoretic generalization of on-line learning and an application to boosting
Y. Freund and R. E. Schapire · 1997
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Mixture density estimation
A Barron and J Li · 1997
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Annealed importance sampling
R. M. Neal · 2001
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Self supervised boosting
Max Welling, Richard S. Zemel, and Geoffrey E. Hinton · 2002
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Boosting density estimation
Saharon Rosset and Eran Segal · 2002
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Jensen-shannon divergence and hilbert space embedding
Bent Fuglede and Flemming Topsoe · 2004
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Hilbertian metrics and positive definite kernels on probability measures
Matthias Hein and Olivier Bousquet · 2005
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Learning generative models via discriminative approaches
Zhuowen Tu · 2007
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Statistical Decision Theory
F. Liese and K.-J. Miescke · 2008
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Information, divergence and risk for binary experiments
M. D. Reid and R. C. Williamson · 2011
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
Cited alongside, same era.
Auto-encoding variational Bayes
D. P. Kingma and M. Welling · 2014
Cited alongside, same era.
Mode regularized generative adversarial networks
Tong Che, Yanran Li, Athul Paul Jacob, Yoshua Bengio, and Wenjie Li · 2016
Cited alongside, same era.
Boosted generative models
Aditya Grover and Stefano Ermon · 2016
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Ensembles of generative adversarial networks
Yaxing Wang, Lichao Zhang, and Joost van de Weijer · 2016
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On the quantitative analysis of decoder-based generative models, 2016
Yuhuai Wu, Yuri Burda, Ruslan Salakhutdinov, and Roger Grosse · 2016
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Unsupervised representation learning with deep convolutional generative adversarial networks
A. Radford, L. Metz, and S. Chintala · 2016
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Infogan: Interpretable representation learning by information maximizing generative adversarial nets
Xi Chen, Yan Duan, Rein Houthooft, John Schulman, Ilya Sutskever, and Pieter Abbeel · 2016
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f-GAN: Training generative neural samplers using variational divergence minimization
Sebastian Nowozin, Botond Cseke, and Ryota Tomioka · 2016
Cited alongside, same era.
Martin Arjovsky, Soumith Chintala, and Léon Bottou · 2017
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Unrolled generative adversarial networks
L. Metz, B. Poole, D. Pfau, and J. Sohl-Dickstein · 2017
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