All 7 Variational Autoencoders (VAEs) questions
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How does Variational Autoencoders (VAEs) work

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Answer

It encodes input data into a compact numeric representation, then decodes that representation back into data, learning in the process how to generate new similar examples.
Real-world example A variational autoencoder can generate new handwritten digit images that look similar to a training set of digits.

Common follow-ups: What is Generative AI, How is Variational Autoencoders (VAEs) evaluated in practice, What tools are commonly used for Variational Autoencoders (VAEs)

Generative AI topics: Introduction to Generative AI Generative Adversarial Networks (GANs) Variational Autoencoders (VAEs)
All 7 Variational Autoencoders (VAEs) questions