EVGAN: Optimization of Generative Adversarial Networks Using Wasserstein Distance and Neuroevolution

Author:

Nair Vivek K.,Shunmuga Velayutham C.

Publisher

Springer Singapore

Reference18 articles.

1. Goodfellow, I.J., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., Bengio, Y.: Generative adversarial nets. In: Proceedings of NIPS, vol. 27, pp. 2672–2680 (2014)

2. Goodfellow, I.: NIPS 2016 tutorial: generative adversarial networks (2016). arXiv preprint arXiv:1701.00160

3. Fedus, W., Rosca, M., Lakshminarayanan, B., Dai, A.M., Mohamed, S., Goodfellow, I.: Many paths to equilibrium: GANs do not need to decrease a divergence at every step. In: Proceedings of ICLR 2018 (2018)

4. Radford, A., Metz, L., Chintala, S.: Unsupervised representation learning with deep convolutional generative adversarial networks. In: Conference paper at ICLR 2016 (2016)

5. Mao, X., Li, Q., Xie, H., Lau, R.Y.K., Wang, Z., Smolley, S.P.: Least squares generative adversarial networks. In: Proceedings of CVPR (2017)

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