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We propose the Wasserstein Auto-Encoder (WAE)---a new algorithm for building a generative model of the data distribution.
Gradient-based learning applied to document recognition
Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner · 1998
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Topics in Optimal Transportation
C. Villani · 2003
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Statistical Decision Theory
F. Liese and K.-J. Miescke · 2008
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A kernel two-sample test
A. Gretton, K. M. Borgwardt, M. J. Rasch, B. Schölkopf, and A. J. Smola · 2012
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Representation learning: A review and new perspectives
Y. Bengio, A. Courville, and P. Vincent · 2013
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Sinkhorn distances: Lightspeed computation of optimal transport
M. Cuturi · 2013
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Auto-encoding variational Bayes
D. P. Kingma and M. Welling · 2014
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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
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Adam: A method for stochastic optimization, 2014
D. P. Kingma and J. Lei · 2014
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Unbalanced optimal transport: geometry and kantorovich formulation
Lenaic Chizat, Gabriel Peyré, Bernhard Schmitzer, and François-Xavier Vialard · 2015
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Matthias Liero, Alexander Mielke, and Giuseppe Savaré · 2015
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Generative moment matching networks
Y. Li, K. Swersky, and R. Zemel · 2015
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Training generative neural networks via maximum mean discrepancy optimization
G. K. Dziugaite, D. M. Roy, and Z. Ghahramani · 2015
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On the high-dimensional power of a linear-time two sample test under mean-shift alternatives
R. Reddi, A. Ramdas, A. Singh, B. Poczos, and L. Wasserman · 2015
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Deep learning face attributes in the wild
Ziwei Liu, Ping Luo, Xiaogang Wang, and Xiaoou Tang · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift, 2015
S. Ioffe and C. Szegedy · 2015
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Adversarial autoencoders
A. Makhzani, J. Shlens, N. Jaitly, and I. Goodfellow · 2016
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f-GAN: Training generative neural samplers using variational divergence minimization
Sebastian Nowozin, Botond Cseke, and Ryota Tomioka · 2016
From optimal transport to generative modeling: the VEGAN cookbook, 2017
O. Bousquet, S. Gelly, I. Tolstikhin, C. J. Simon-Gabriel, and B. Schölkopf · 2017
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Wasserstein GAN, 2017
M. Arjovsky, S. Chintala, and L. Bottou · 2017
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Improved training of wasserstein GANs, 2017
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Adversarial variational bayes: Unifying variational autoencoders and generative adversarial networks, 2017
L. Mescheder, S. Nowozin, and A. Geiger · 2017
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InfoVAE: Information maximizing variational autoencoders, 2017
S. Zhao, J. Song, and S. Ermon · 2017
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Energy-based generative adversarial network
J. Zhao, M. Mathieu, and Y. LeCun · 2017
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Elbo surgery: yet another way to carve up the variational evidence lower bound
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Stochastic optimization for large-scale optimal transport
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Unsupervised representation learning with deep convolutional generative adversarial networks
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Identity mappings in deep residual networks
K. He, X. Zhang, S. Ren, and J. Sun · 2016
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Improved generator objectives for GANs, 2016
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Adversarially learned inference
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GANs trained by a two time-scale update rule converge to a nash equilibrium
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