This blog post is an overview of the perspectives on diffusion I’ve found useful.
Diffusion models are autoencoders
Diffusion models are deep latent variable models
Diffusion models predict the score function
Diffusion models solve reverse SDEs
Diffusion models are flow-based models
Diffusion models are recurrent neural networks
Diffusion models are autoregressive models
Diffusion models estimate expectations