Advanced Deep Learning with Keras

Variational Autoencoders (VAEs)
Figures 8.3.1 and 8.3.2 show the latent vector means for β -VAE with β = 7 and β = 10 .
With β = 7 , the distribution has a smaller standard deviation when compared to
CVAE. With β = 10 , there is only the latent code that is learned. The distribution
is practically shrunk to 1D with the first latent code z[0] ignored by the encoder
and decoder:
Figure 8.3.2: The latent vector mean values for the test dataset ( β -VAE with )
Color images can be found on the book GitHub repository: https://github.com/PacktPublishing/Advanced-
Deep-Learning-with-Keras/tree/master/chapter8-vae.
These observations are reflected in Figure 8.3.3. β -VAE with β = 7 has two latent
codes that are practically independent. z[0] determines the tilt of the writing style.
Meanwhile, z[1] specifies the width and roundness (if applicable) of the digits.
For β -VAE with β = 10 , z[0] is muted. Increasing z[0] does not alter the digit in
a significant way. z[1] determines the tilt angle and width of the writing style.
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