Deep learning, Autoencoder

• https://en.wikipedia.org/wiki/Generative_adversarial_networks

Key ideas #

• Paper/Goodfellow2014

In the proposed adversarial nets framework, the generative model is pitted against an adversary: a discriminative model that learns to determine whether a sample is from the model distribution or the data distribution. The generative model can be thought of as analogous to a team of counterfeiters, trying to produce fake currency and use it without detection, while the discriminative model is analogous to the police, trying to detect the counterfeit currency. Competition in this game drives both teams to improve their methods until the counterfeits are indistiguishable from the genuine articles.

Tutorials #

• How do GANs intuitively work?
• NIPS 2016 Tutorial: Generative Adversarial Networks

Applications #

Image completion #

• http://bamos.github.io/2016/08/09/deep-completion/

Incoming Links #

Related Articles (Article 0) #

• Generative adversarial network

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