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Recent work has shown local convergence of GAN training for absolutely continuous data and generator distributions.
Nonlinear systems
Khalil, H. K · 1996
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Nonlinear programming
Bertsekas, D. P · 1999
Earlier work this paper cites.
Learning multiple layers of features from tiny images
Krizhevsky, A. and Hinton, G · 2009
Earlier work this paper cites.
Lecture 6.5-rmsprop: Divide the gradient by a running average of its recent magnitude, 2012
Tieleman, T. and Hinton, G · 2012
Earlier work this paper cites.
Generative adversarial nets
Goodfellow, I. J., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A. C., and Bengio, Y · 2014
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Deep learning face attributes in the wild
Liu, Z., Luo, P., Wang, X., and Tang, X · 2015
Earlier work this paper cites.
Unsupervised representation learning with deep convolutional generative adversarial networks
Radford, A., Metz, L., and Chintala, S · 2015
Earlier work this paper cites.
ImageNet Large Scale Visual Recognition Challenge
Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., Berg, A. C., and Fei-Fei, L · 2015
Earlier work this paper cites.
LSUN: construction of a large-scale image dataset using deep learning with humans in the loop
Yu, F., Zhang, Y., Song, S., Seff, A., and Xiao, J · 2015
Earlier work this paper cites.
Tensorflow: A system for large-scale machine learning
Abadi, M., Barham, P., Chen, J., Chen, Z., Davis, A., Dean, J., Devin, M., Ghemawat, S., Irving, G., Isard, M., Kudlur, M., Levenberg, J., Monga, R., Moore, S., Murray, D. G., Steiner, B., Tucker, P. A., Vasudevan, V., Warden, P., Wicke, M., Yu, Y., and Zheng, X · 2016
Earlier work this paper cites.
Deep residual learning for image recognition
He, K., Zhang, X., Ren, S., and Sun, J · 2016
Earlier work this paper cites.
f-gan: Training generative neural samplers using variational divergence minimization
Nowozin, S., Cseke, B., and Tomioka, R · 2016
Cited alongside, same era.
Improved techniques for training gans
Salimans, T., Goodfellow, I. J., Zaremba, W., Cheung, V., Radford, A., and Chen, X · 2016
Cited alongside, same era.
Amortised MAP inference for image super-resolution
Sønderby, C. K., Caballero, J., Theis, L., Shi, W., and Huszár, F · 2016
Cited alongside, same era.
Towards principled methods for training generative adversarial networks
Arjovsky, M. and Bottou, L · 2017
Cited alongside, same era.
Arjovsky, M., Chintala, S., and Bottou, L · 2017
Cited alongside, same era.
Kodali, N., Abernethy, J. D., Hays, J., and Kira, Z · 2017
Later among the works it cites.
The numerics of gans
Mescheder, L. M., 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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Conditional image synthesis with auxiliary classifier gans
Odena, A., Olah, C., and Shlens, J · 2017
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Stabilizing training of generative adversarial networks through regularization
Roth, K., Lucchi, A., Nowozin, S., and Hofmann, T · 2017
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Berthelot, D., Schumm, T., and Metz, L · 2017
Cited alongside, same era.
Improved training of wasserstein gans
Gulrajani, I., Ahmed, F., Arjovsky, M., Dumoulin, V., and Courville, A. C · 2017
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.
Boundary-seeking generative adversarial networks
Hjelm, R. D., Jacob, A. P., Che, T., Cho, K., and Bengio, Y · 2017
Cited alongside, same era.
Progressive growing of gans for improved quality, stability, and variation
Karras, T., Aila, T., Laine, S., and Lehtinen, J · 2017
Cited alongside, same era.
Zhao, J. J., Mathieu, M., and LeCun, Y · 2017
Later among the works it cites.
Barratt, S. and Sharma, R · 2018
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A variational inequality perspective on generative adversarial nets
Gidel, G., Berard, H., Vincent, P., and Lacoste-Julien, 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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The unusual effectiveness of averaging in GAN training
Yazici, Y., Foo, C. S., Winkler, S., Yap, K., Piliouras, G., and Chandrasekhar, V · 2018
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