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Generative adversarial networks (GANs) are effective in generating realistic images but the training is often unstable.
Linear systems , volume 156
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Generative adversarial nets
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Deep learning face attributes in the wild
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Unsupervised representation learning with deep convolutional generative adversarial networks
Radford, A., Metz, L., and Chintala, S · 2015
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Laplace transform (PMS-6)
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Infogan: Interpretable representation learning by information maximizing generative adversarial nets
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Goodfellow, I · 2016
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Deep residual learning for image recognition
He, K., Zhang, X., Ren, S., and Sun, J · 2016
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Improved techniques for training gans
Salimans, T., Goodfellow, I., Zaremba, W., Cheung, V., Radford, A., and Chen, X · 2016
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Wasserstein generative adversarial networks
Arjovsky, M., Chintala, S., and Bottou, L · 2017
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Understanding gans: the lqg setting
Feizi, S., Farnia, F., Ginart, T., and Tse, D · 2017
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Improved training of wasserstein gans
Gulrajani, I., Ahmed, F., Arjovsky, M., Dumoulin, V., and Courville, A. C · 2017
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Triple generative adversarial nets
Li, C., Xu, T., Zhu, J., and Zhang, B · 2017
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Large scale gan training for high fidelity natural image synthesis
Brock, A., Donahue, J., and Simonyan, K · 2018
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Sgan: An alternative training of generative adversarial networks
Chavdarova, T. and Fleuret, F · 2018
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Learning implicit generative models by teaching explicit ones
Du, C., Xu, K., Li, C., Zhu, J., and Zhang, B · 2018
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Negative momentum for improved game dynamics
Gidel, G., Hemmat, R. A., Pezeshki, M., Lepriol, R., Huang, G., Lacoste-Julien, S., and Mitliagkas, I · 2018
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Composite functional gradient learning of generative adversarial models
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Least squares generative adversarial networks
Mao, X., Li, Q., Xie, H., Lau, R. Y., Wang, Z., and Paul Smolley, S · 2017
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The numerics of gans
Mescheder, L., Nowozin, S., and Geiger, A · 2017
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Gradient descent gan optimization is locally stable
Nagarajan, V. and Kolter, J. Z · 2017
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Lr-gan: Layered recursive generative adversarial networks for image generation
Yang, J., Kannan, A., Batra, D., and Parikh, D · 2017
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A pid controller approach for stochastic optimization of deep networks
An, W., Wang, H., Sun, Q., Xu, J., Dai, Q., and Zhang, L · 2018
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Johnson, R. and Zhang, T · 2018
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A large-scale study on regularization and normalization in gans
Kurach, K., Lucic, M., Zhai, X., Michalski, M., and Gelly, S · 2018
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Generative adversarial network training is a continual learning problem
Liang, K. J., Li, C., Wang, G., and Carin, L · 2018
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Which training methods for gans do actually converge?
Mescheder, L., Geiger, A., and Nowozin, S · 2018
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Spectral normalization for generative adversarial networks
Miyato, T., Kataoka, T., Koyama, M., and Yoshida, Y · 2018
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Consistency regularization for generative adversarial networks
Zhang, H., Zhang, Z., Odena, A., and Lee, H · 2018
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Large scale adversarial representation learning
Donahue, J. and Simonyan, K · 2019
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