[SleekEagle]

One use case is in the training of Diffusion Models. In the original formulation, the likelihood-maximizing objective is recast in terms of KL divergences. This is done because the KL divergence between Gaussians has a closed form, and the transition distributions in Diffusion Models are taken to be Gaussian, which makes the problem tenable.

https://www.assemblyai.com/blog/diffusion-models-for-machine...