De Yuting Wei
Apparaît dans la collection : New challenges in high-dimensional statistics / Statistique mathématique 2025
Score-based diffusion models, while achieving remarkable empirical performance, often suffer from low sampling speed, due to extensive function evaluations needed during the sampling phase. Despite a flurry of recent activities towards speeding up diffusion generative modeling in practice, theoretical underpinnings for acceleration techniques remain severely limited. In this talk, we discuss novel training-free algorithms to accelerate popular deterministic (i.e., DDIM) and stochastic (i.e., DDPM) samplers.
De Matthew Juniper
De Yiannis Vlassopoulos
