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Also, the white paper on TensorFlow Distributions contains many neat examples which demonstrate how easy it is to go from the most basic VAE to the state-of-the-art architecture that uses a PixelCNN++ decoder and inverse autoregressive flows for the encoder and prior. Might be good for comparison or just a source of inspiration :)
This may not be the best framework for it, but it would be a good exercise to see how it looks compared to competing frameworks, e.g. Keras, Edward.
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