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Variational Autoencoders

Like autoencoders, but penalize latent variables for deviating from a Gaussian distribution.


See also:

can be calculated using our decoder neural network, which generates images by taking samples from the latent space .

is our prior over the latent space (usually a unit Gaussian).

is difficult to calculate because it requires calculating for all possible values of .

is the variational posterior, parameterized by a second set of parameters , which approximates the true posterior distribution .

Additional resources