Batch norm with entropic regularization turns deterministic autoencoders into generative models

25 Feb 2020 Amur Ghose Abdullah Rashwan Pascal Poupart

The variational autoencoder is a well defined deep generative model that utilizes an encoder-decoder framework where an encoding neural network outputs a non-deterministic code for reconstructing an input. The encoder achieves this by sampling from a distribution for every input, instead of outputting a deterministic code per input... (read more)

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