Recently I checked again the Word Models interactive paper. They use a VAE to compress 64x64x3 images to 32 dim latent vectors. But on the site there is an interactive demo where I can set 15 values of the latent vector which will be decompressed. I guess these are the most important features out of the 32.
The question is, how can I rank the features by reconstruction variance (or I don8217;t really know how to call this)?
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