Batch norm with entropic regularization turns deterministic autoencoders into generative models
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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Methods used in the Paper
| METHOD | TYPE | |
|---|---|---|
AutoEncoder
|
Generative Models | |
Batch Normalization
|
Normalization |