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Paper: Updated with results and conclusion
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‎Final_Report/images/discriminator_layers.png

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‎Final_Report/images/generator_layers.png

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‎Paper/fyp.aux

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\@writefile{toc}{\contentsline {section}{\numberline {A}Final Thoughts on Good Layout}{6}}
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‎Paper/fyp.bbl

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\begin{thebibliography}{10}
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\bibitem{wgan}
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M.~Arjovsky, S.~Chintala, and L.~Bottou.
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\newblock {W}asserstein generative adversarial networks.
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\newblock In D.~Precup and Y.~W. Teh, editors, {\em Proceedings of the 34th
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International Conference on Machine Learning}, volume~70 of {\em Proceedings
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of Machine Learning Research}, pages 214--223, International Convention
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Centre, Sydney, Australia, 06--11 Aug 2017. PMLR.
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\bibitem{infogan}
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X.~Chen, X.~Chen, Y.~Duan, R.~Houthooft, J.~Schulman, I.~Sutskever, and
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P.~Abbeel.
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\newblock Infogan: Interpretable representation learning by information
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maximizing generative adversarial nets.
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\newblock In D.~D. Lee, M.~Sugiyama, U.~V. Luxburg, I.~Guyon, and R.~Garnett,
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editors, {\em Advances in Neural Information Processing Systems 29}, pages
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2172--2180. Curran Associates, Inc., 2016.
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\bibitem{improvedwgan}
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I.~Gulrajani, F.~Ahmed, M.~Arjovsky, V.~Dumoulin, and A.~C. Courville.
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\newblock Improved training of wasserstein gans.
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\newblock In I.~Guyon, U.~V. Luxburg, S.~Bengio, H.~Wallach, R.~Fergus,
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S.~Vishwanathan, and R.~Garnett, editors, {\em Advances in Neural Information
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Processing Systems 30}, pages 5767--5777. Curran Associates, Inc., 2017.
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\bibitem{deepresidual}
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K.~He, X.~Zhang, S.~Ren, and J.~Sun.
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\newblock Deep residual learning for image recognition.
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\newblock {\em CoRR}, abs/1512.03385, 2015.
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\bibitem{imagenet}
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A.~Krizhevsky, I.~Sutskever, and G.~E. Hinton.
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\newblock Imagenet classification with deep convolutional neural networks.
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\newblock In F.~Pereira, C.~J.~C. Burges, L.~Bottou, and K.~Q. Weinberger,
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editors, {\em Advances in Neural Information Processing Systems 25}, pages
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1097--1105. Curran Associates, Inc., 2012.
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\bibitem{copgan}
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M.-Y. Liu and O.~Tuzel.
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\newblock Coupled generative adversarial networks.
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\newblock In D.~D. Lee, M.~Sugiyama, U.~V. Luxburg, I.~Guyon, and R.~Garnett,
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editors, {\em Advances in Neural Information Processing Systems 29}, pages
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469--477. Curran Associates, Inc., 2016.
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\bibitem{congan}
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M.~Mirza and S.~Osindero.
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\newblock Conditional generative adversarial nets.
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\newblock {\em CoRR}, abs/1411.1784, 2014.
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\bibitem{vardivmin}
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S.~Nowozin, B.~Cseke, and R.~Tomioka.
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\newblock f-gan: Training generative neural samplers using variational
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divergence minimization.
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\newblock In D.~D. Lee, M.~Sugiyama, U.~V. Luxburg, I.~Guyon, and R.~Garnett,
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editors, {\em Advances in Neural Information Processing Systems 29}, pages
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271--279. Curran Associates, Inc., 2016.
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\bibitem{acgan}
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A.~Odena, C.~Olah, and J.~Shlens.
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\newblock Conditional image synthesis with auxiliary classifier gans.
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\newblock {\em arXiv preprint arXiv:1610.09585}, 2016.
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\bibitem{dcgan}
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A.~Radford, L.~Metz, and S.~Chintala.
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\newblock Unsupervised representation learning with deep convolutional
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generative adversarial networks.
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\newblock {\em CoRR}, abs/1511.06434, 2015.
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\bibitem{capsnet}
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S.~Sabour, N.~Frosst, and G.~E. Hinton.
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\newblock Dynamic routing between capsules.
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\newblock In I.~Guyon, U.~V. Luxburg, S.~Bengio, H.~Wallach, R.~Fergus,
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S.~Vishwanathan, and R.~Garnett, editors, {\em Advances in Neural Information
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Processing Systems 30}, pages 3856--3866. Curran Associates, Inc., 2017.
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\bibitem{improvedgan}
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T.~Salimans, I.~Goodfellow, W.~Zaremba, V.~Cheung, A.~Radford, X.~Chen, and
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X.~Chen.
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\newblock Improved techniques for training gans.
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\newblock In D.~D. Lee, M.~Sugiyama, U.~V. Luxburg, I.~Guyon, and R.~Garnett,
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editors, {\em Advances in Neural Information Processing Systems 29}, pages
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2234--2242. Curran Associates, Inc., 2016.
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\end{thebibliography}

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‎Paper/fyp.dvi

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