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Generative models with an encoding component such as autoencoders currently receive great interest.
Gradient-Based Learning Applied to Document Recognition
Lecun, Y., Bottou, L., Bengio, Y., and Haffner, P · 1998
Earlier work this paper cites.
Displacement Interpolation Using Lagrangian Mass Transport
Bonneel, N., van de Panne, M., Paris, S., and Heidrich, W · 2011
Earlier work this paper cites.
Deep sparse rectifier neural networks
Glorot, X., Bordes, A., and Bengio, Y · 2011
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A Kernel Two-Sample Test
Gretton, A., Borgwardt, K. M., Rasch, M. J., Schölkopf, B., and Smola, A · 2012
Earlier work this paper cites.
Generative Adversarial Nets
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., and Bengio, Y · 2014
Earlier work this paper cites.
Auto-Encoding Variational Bayes
Kingma, D. P. and Welling, M · 2014
Earlier work this paper cites.
NICE: Non-linear Independent Components Estimation
Dinh, L., Krueger, D., and Bengio, Y · 2015
Earlier work this paper cites.
Deep Learning Face Attributes in the Wild
Liu, Z., Luo, P., Wang, X., and Tang, X · 2015
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Adversarially Learned Inference
Dumoulin, V., Belghazi, I., Poole, B., Mastropietro, O., Lamb, A., Arjovsky, M., and Courville, A · 2016
Earlier work this paper cites.
Makhzani, A., Shlens, J., Jaitly, N., Goodfellow, I., and Frey, B · 2016
Earlier work this paper cites.
Understanding and improving convolutional neural networks via concatenated rectified linear units
Shang, W., Sohn, K., Almeida, D., and Lee, H · 2016
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Arjovsky, M., Chintala, S., and Bottou, L · 2017
Earlier work this paper cites.
The Cramer Distance as a Solution to Biased Wasserstein Gradients
Bellemare, M. G., Danihelka, I., Dabney, W., Mohamed, S., Lakshminarayanan, B., Hoyer, S., and Munos, R · 2017
Cited alongside, same era.
Comparison of Maximum Likelihood and GAN-based training of Real NVPs
Danihelka, I., Lakshminarayanan, B., Uria, B., Wierstra, D., and Dayan, P · 2017
Cited alongside, same era.
Density estimation using Real NVP
Dinh, L., Sohl-Dickstein, J., and Bengio, S · 2017
Cited alongside, same era.
Donahue, J., Krähenbühl, P., and Darrell, T · 2017
Cited alongside, same era.
The Reversible Residual Network: Backpropagation Without Storing Activations
Gomez, A. N., Ren, M., Urtasun, R., and Grosse, R. B · 2017
Demystifying MMD GANs
Bińkowski, M., Sutherland, D. J., Arbel, M., and Gretton, A · 2018
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Flow-GAN: Combining Maximum Likelihood and Adversarial Learning in Generative Models
Grover, A., Dhar, M., and Ermon, S · 2018
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i-RevNet: Deep Invertible Networks
Jacobsen, J.-H., Smeulders, A. W. M., and Oyallon, E · 2018
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Progressive Growing of GANs for Improved Quality, Stability, and Variation
Karras, T., Aila, T., Laine, S., and Lehtinen, J · 2018
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Sliced-Wasserstein Autoencoder: An Embarrassingly Simple Generative Model
Kolouri, S., Martin, C. E., and Rohde, G. K · 2018
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Cited alongside, same era.
GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
Heusel, M., Ramsauer, H., Unterthiner, T., Nessler, B., and Hochreiter, S · 2017
Cited alongside, same era.
Image-to-Image Translation with Conditional Adversarial Networks
Isola, P., Zhu, J. Y., Zhou, T., and Efros, A. A · 2017
Cited alongside, same era.
MMD GAN: Towards Deeper Understanding of Moment Matching Network
Li, C.-L., Chang, W.-C., Cheng, Y., Yang, Y., and Poczos, B · 2017
Cited alongside, same era.
Lim, J. H. and Ye, J. C · 2017
Cited alongside, same era.
Are GANs Created Equal? A Large-Scale Study
Lucic, M., Kurach, K., Michalski, M., Gelly, S., and Bousquet, O · 2017
Cited alongside, same era.
Adversarial Generator-Encoder Networks
Ulyanov, D., Vedaldi, A., and Lempitsky, V · 2017
Cited alongside, same era.
Miyato, T., Kataoka, T., Koyama, M., and Yoshida, Y · 2018
Closest in time.
Computational Optimal Transport
Peyré, G. and Cuturi, M · 2018
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On the Latent Space of Wasserstein Auto-Encoders
Rubenstein, P. K., Schoelkopf, B., and Tolstikhin, I · 2018
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Improving GANs Using Optimal Transport
Salimans, T., Zhang, H., Radford, A., and Metaxas, D · 2018
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Tolstikhin, I., Bousquet, O., Gelly, S., and Schoelkopf, B · 2018
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Self-Attention Generative Adversarial Networks
Zhang, H., Goodfellow, I., Metaxas, D., and Odena, A · 2018
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