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Auto-regressive Generative Models

Examples

  • PixelRNN — Recurrent NN which predicts pixel categories given the previous pixels.
  • PixelCNN — Output pixels are represented as 256 categorical variables. Use a masked convolution to include only preceding pixel information. Faster but lower accuracy than PixelRNN.
  • PixelCNN++ — Instead of representing output pixels as categorical variables, represent output pixels as a set of distributions parameterized by parameters produced by the network.

Additional resources