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Concept
Variational Autoencoder
A
Variational Autoencoder
(VAE) is a type of
generative model
that learns to encode input data into a
latent space
and then decodes it back to reconstruct the
original data
, while also allowing for the generation of
new data samples
. It combines principles of
deep learning
and
Bayesian inference
to produce a continuous and smooth
latent space
, facilitating
efficient sampling
and
interpolation between data points
.
Relevant Degrees
Artificial Intelligence Systems 78%
Computational Mathematics 22%
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