#vae
Latent-variable models trained via the ELBO.
3 chapters, oldest era first: one idea traced across the books.
- From Noise to Image 2013–2015 Ch. 2: Variational Autoencoders The ELBO, the reparameterization trick, and the first neural networks that could imagine — blurrily.
- From Noise to Image 2015–2020 Ch. 8: Diffusion Foundations Forward noising, the ELBO reduced to a simple denoising loss, and score functions — the math under everything modern.
- From Frames to Worlds 2018–2019 Ch. 3: Predicting the Next Frame World-model prehistory: learn a latent simulator, then act inside it.