Stefano Ermon and his PhD student Yang Song began working on score-based generative models in 2019; this work eventually became diffusion models.

“and back then we were very unhappy with the state of generative models for images like the GANs were they they worked but they were very unstable to train very hard to reproduce results and so we were trying to see is there a way to build something that is as good as a GAN but it's more principled and so we started working on score-based the generative models which are basically what eventually became”

“diffusion models back in 2019 with my PhD student Yang Song and so we kind of like came up with this idea of let's train a neural network to denoise images and if you can denoise an image then you really are understanding enough about the structure of the image that it should be possible to build like a generative procedure based on these denoisers and that basically became the kind of like underlying technology of”