Publication | Open Access
NIPS 2016 Tutorial: Generative Adversarial Networks
1.3K
Citations
48
References
2016
Year
Artificial IntelligenceGenerative Artificial IntelligenceEngineeringMachine LearningData ScienceTutorial DescribesGenerative Adversarial NetworkImage-based ModelingGenerative ModelsNips 2016Generative ModelComputer ScienceGenerative AiGenerative ModelingDeep LearningGenerative SystemComputer Vision
This report summarizes the tutorial presented by the author at NIPS 2016 on generative adversarial networks (GANs). The tutorial describes: (1) Why generative modeling is a topic worth studying, (2) how generative models work, and how GANs compare to other generative models, (3) the details of how GANs work, (4) research frontiers in GANs, and (5) state-of-the-art image models that combine GANs with other methods. Finally, the tutorial contains three exercises for readers to complete, and the solutions to these exercises.
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