Speaker: Kangwook Lee
Title: Score-based Generative Modeling Secretly Minimizes the Wasserstein Distance
Abstract: In this talk, I’ll present the findings from my recent research on score-based diffusion models. I’ll start with a gentle overview of these models, which are well known for DALL-E and stable diffusion models. I’ll then share my latest discovery that score-based diffusion models are secretly minimizing the Wasserstein distance between the generated and data distributions. I’ll explain the significance of this result and provide numerical evidence to support it. I’ll also briefly touch on ongoing projects, including our faster sampling algorithm and open problems. This presentation is based on the collaborative work with Dohyun Kwon and Ying Fan.