Scalable Diffusion Models with Transformers (DiT)
	

Overview
	
Scalable Diffusion Models with Transformers (DiT) by William Peebles and Saining Xie.
The abstract of the paper is the following:
We explore a new class of diffusion models based on the transformer architecture. We train latent diffusion models of images, replacing the commonly-used U-Net backbone with a transformer that operates on latent patches. We analyze the scalability of our