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Model Architectures · Go deeper

VAEs (Variational Autoencoders)

Compress data into a smooth 'concept space' you can sample and interpolate — the quiet engine inside Stable Diffusion.

  • 40 min lesson
  • advanced level
  • Narrated presentation

What you’ll learn

  • Encoder-decoder bottleneck
  • Latent space
  • Probabilistic encoding (mean + variance)
  • KL regularization
  • Interpolation and sampling
  • Role in latent diffusion

Inside this lesson

A narrated, slide-by-slide presentation with 1 prediction exercise, 1 knowledge check, 2 videos. You answer as you go, and the platform checks your work.

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