The model that combines Markov processes and variational inference achieves FID3.17(SOTA) at unconditional CIFAR10. It is an AutoEncoder-like model, but with each layer considered as a stochastic process and parameterize the noise to be applied there.
TL;DR
The model that combines Markov processes and variational inference achieves FID3.17(SOTA) at unconditional CIFAR10. It is an AutoEncoder-like model, but with each layer considered as a stochastic process and parameterize the noise to be applied there.![image](https://user-images.githubusercontent.com/24524018/92562018-3e344400-f2b0-11ea-8218-6dfa812d4674.png)
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https://arxiv.org/abs/2006.11239
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