Over the past three years, diffusion models have established themselves as a new generative modeling paradigm. Their empirical successes have broadened the applications of generative modeling to image, video, audio, 3D synthesis, science applications, and more. As diffusion models become more and more popular and are applied to extremely diverse problems, it also becomes harder to follow the key contributions in the field. This workshop aims to keep track of recent advances and identify guidelines for future research. By bringing together practice, methodology, and theory actors we aim to identify unexplored areas, foster collaboration, and push the frontier of diffusion model research.