@PREAMBLE{
 "\providecommand{\noopsort}[1]{}" 
 # "\providecommand{\singleletter}[1]{#1}%" 
}

@misc{goodfellow2014generative,
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    year={2014},
    eprint={1406.2661},
    archivePrefix={arXiv},
    primaryClass={stat.ML}
}

@misc{arjovsky2017wasserstein,
    title={Wasserstein GAN},
    author={Martin Arjovsky and Soumith Chintala and Léon Bottou},
    year={2017},
    eprint={1701.07875},
    archivePrefix={arXiv},
    primaryClass={stat.ML}
}


@misc{radford2015unsupervised,
    title={Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks},
    author={Alec Radford and Luke Metz and Soumith Chintala},
    year={2015},
    eprint={1511.06434},
    archivePrefix={arXiv},
    primaryClass={cs.LG}
}

@article{widrow1962generalization,
  title={Generalization and Information Storage in Networks of ADALINE Neurons. Self Organizing Systems},
  author={Widrow, Bernard},
  journal={Yovitz, MC, Jacobi, GT, and Goldstein, GD editors},
  pages={435--461},
  year={1962}
}


@ARTICLE{overviewDocument,
    author={Z. {Pan} and W. {Yu} and X. {Yi} and A. {Khan} and F. {Yuan} and Y. {Zheng}},
    journal={IEEE Access},
    title={Recent Progress on Generative Adversarial Networks (GANs): A Survey},
    year={2019},
    volume={7},
    number={},
    pages={36322-36333},
    keywords={artificial intelligence;neural nets;generative adversarial network;GANs;generative models;data generation capacity;artificial intelligence;Gallium nitride;Generators;Generative adversarial networks;Training;Feature extraction;Data models;Unsupervised learning;Deep learning;machine learning;unsupervised learning;generative adversarial networks},
    doi={10.1109/ACCESS.2019.2905015},
    ISSN={2169-3536},
month={},}