Translations:Generative Adversarial Nets/5/en

Goodfellow et al. proposed a fundamentally different approach: instead of explicitly modeling the data distribution, train a generator network to produce samples that fool a discriminator network trained to tell real from fake. This adversarial formulation avoids the need for explicit density estimation, approximate inference, or Markov chains, requiring only backpropagation through both networks.