Autoencoders

Thu, 09 Jul 2026 21:02:56 +1000

an autoencoder is a network trained to do the one thing that sounds useless: output its own input. the trick is the obstacle course in the middle — a bottleneck, a corruption, a penalty — that makes verbatim copying impossible, so the network is forced to learn what about the input is worth keeping. 𐃏 the family tree below runs from the linear special case (which is pca wearing a trenchcoat) to the variational autoencoder, which turns the whole construction into a generative model (Goodfellow, Ian, 2016).

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Autoencoders