Generative Adversarial Networks: A Comprehensive Review

Author:

Kotha Pavani,Janardhan Babu V.,Ankam Sreejyothsna

Publisher

Springer Nature Singapore

Reference18 articles.

1. Raj VB, Hareesh K (2020) Review on generative adversarial networks. In: 2020 international conference on communication and signal processing (ICCSP), Chennai, pp 0479–0482. https://doi.org/10.1109/ICCSP48568.2020.9182058

2. Salimans T, Goodfellow I, Zaremba W, Cheung V, Radford A, Chen X (2016) Improved techniques for training GANs. In: Proceedings of the 30th international conference on neural information processing systems, NIPS’16, Barcelona, Spain, Dec 2016. Curran Associates Inc., pp 2234–2242. ISBN 978-1-5108-3881-9

3. Radford A, Metz L, Chintala S (2015) Unsupervised representation learning with deep convolutional generative adversarial networks. arXiv preprint arXiv:1511.06434

4. Gulrajani I et al (2017) Improved training of Wasserstein GANs. Adv Neural Inf Process Syst 30

5. Heusel M et al (2017) GANs trained by a two time-scale update rule converge to a local Nash equilibrium. In: NIPS

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