GAN is the most interesting idea


Fig.1- Generative Adversial Networks[1].


Generative Adversarial Networks (GANs) are neural nets which were first introduced by Ian Goodfellow in 2014. In GAN, two models are simultaneously trained: a generative model G that captures the data distribution, and a discriminative model D that estimates the probability that a sample came from the training data rather than G.

 

Source:

[1]: https://hackernoon.com/generative-adversarial-networks-a-deep-learning-a...

[2]: Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A. and Bengio, Y., 2014. Generative adversarial nets. In Advances in neural information processing systems (pp. 2672-2680).