Variational Autoencoder
A generative model where the encoder maps inputs to a probability distribution (mean and variance) in the latent space, forcing the latent space to have a structured, typically Gaussian, form.
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Videos Mentioning Variational Autoencoder
Stanford CME296 Diffusion & Large Vision Models | Spring 2026 | Lecture 4 - Latent Space & Guidance
Stanford Online
A generative model where the encoder maps inputs to a probability distribution (mean and variance) in the latent space, forcing the latent space to have a structured, typically Gaussian, form.
Stanford CME296 Diffusion & Large Vision Models | Spring 2026 | Lecture 5 - Architectures
Stanford Online
An architecture for representing images in a meaningful latent space, structuring it with constraints on distribution behavior, but can lead to blurry images.
Stanford CME296 Diffusion & Large Vision Models | Spring 2026 | Lecture 8 - Trending Topics
Stanford Online
A model used to learn a structured latent space for images by compressing information into fewer dimensions, making it easier for generative models to learn. It uses an Evidence Lower Bound (ELBO) loss.