This course provides a comprehensive introduction to diffusion models and flow models for generative AI, covering both theoretical foundations and methodological advancements. The course is divided ...

Abstract: This paper introduces a diffusion model that replaces the target prior distribution from a standard Gaussian to non-zero-mean Gaussian priors, with shifted latent trajectories determined by ...

Previous high-order solvers are unstable for guided sampling: Samples use the pre-trained DPMs on ImageNet 256 256 with a classifier guidance scale 8.0, varying different samplers (and different ...

Abstract: Despite strong performances on many generative tasks, diffusion and flow matching models require a large number of sampling steps to generate high-quality images. This has motivated the ...

We provide the official Pytorch implementation of the paper Ambiguous Medical Image Segmentation using Diffusion Models The implementation of diffusion model segmentation model presented in the paper ...