From Autoencoder to Beta-VAE | Lil'Log
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2026-07-15 10:01:31
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Text Highlight2026-07-15 13:22:31
Original Highlight Excerpt
"The idea of Variational Autoencoder (Kingma & Welling, 2014), short for VAE, is actually less similar to all the autoencoder models above, but deeply rooted…"
Whisper Note
Wait, so calling it an autoencoder is kind of a misnomer then?
Text Highlight2026-07-15 13:13:31
Original Highlight Excerpt
"The idea of Variational Autoencoder (Kingma & Welling, 2014), short for VAE, is actually less similar to all the autoencoder models above, but deeply rooted…"
Whisper Note
So it's more Bayesian than autoencoder, that explains the math-heavy derivations.
Text Highlight2026-07-15 10:19:31
Original Highlight Excerpt
"Autocoder is invented to reconstruct high-dimensional data using a neural network model with a narrow bottleneck layer"
Whisper Note
Haha 'probably not true' — honest but then why even mention it?
Text Highlight2026-07-15 10:10:31
Original Highlight Excerpt
"Autocoder is invented to reconstruct high-dimensional data using a neural network model with a narrow bottleneck layer"
Whisper Note
The bottleneck trick is neat, but I always wonder how much info we lose.
Text Highlight2026-07-15 10:01:31
Original Highlight Excerpt
"Autocoder is invented to reconstruct high-dimensional data using a neural network model with a narrow bottleneck layer"
Whisper Note
Wait, is it autocoder or autoencoder? typo? anyway good intro
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