CODEWITHSUNDEEP
deep-learninglog-likelihood
Value_Investor
Value_Investor

Reputation: 175

Why does a conditional VAE not ignore the condition?

A variational autoencoder optimizes the ELBo objective:

ELBo

In no way is ELBo based on a joint or factorized probability distribution of two variables x and y. Therefore, the encoder of a conditional VAE seems to be able to ignore y (the condition) entirely, and merely retain the information required for reconstructing x (the image). Similarly, the decoder seems to be able to ignore y and merely extract the information from the latent sample required for reconstructing x. Given a setup such as the picture below (courtesy of Montserrat, Bustamante & Ioannidis), why is this not a more frequently occurring problem? Is it because the condition may provide a significant amount of representation in a simple form?

setup

Upvotes: 1

Views: 159

Answers (1)

Ori
Ori

Reputation: 1

Therefore, the encoder of a conditional VAE seems to be able to ignore y (the condition) entirely,

My intuition might be wrong, but how about remove the condition into the decoder. Feel like it will force the encoder to compress the condition into z.

the decoder seems to be able to ignore y and merely extract the information from the latent sample required for reconstructing x

Does it relates to the posterior collapse? I see paper also uses the term: representation collapse. I don't see a general solution if that happens.

Upvotes: 0

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