GANGogh: Creating Art with GANs – Towards Data Science – Medium

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The work here presented is the result of a semester long independent research performed by Kenny Jones and Derrick Bonafilia (both Williams College 2017) under the guidance of Professor Andrea Danyluk. Kenny and Derrick are both heading to Facebook next year as Software Engineers and hope to continue studying GANs in whatever capacity is available to them. Generative Adversarial Networks (GANS) were introduced by Ian Goodfellow et. GANs address the lack of relative success of deep generative models compared to deep discriminative models. The authors cite the intractable nature of the maximum likelihood estimation that is necessary for most generative models as the reason for this discrepancy.