Opportunities and challenges of diffusion models for generative AI
Diffusion models, a powerful and universal generative artificial intelligence technology, have
achieved tremendous success and opened up new possibilities in diverse applications. In …
achieved tremendous success and opened up new possibilities in diverse applications. In …
Dynamical regimes of diffusion models
We study generative diffusion models in the regime where both the data dimension and the
sample size are large, and the score function is trained optimally. Using statistical physics …
sample size are large, and the score function is trained optimally. Using statistical physics …
An overview of diffusion models: Applications, guided generation, statistical rates and optimization
Stochastic runge-kutta methods: Provable acceleration of diffusion models
Diffusion models play a pivotal role in contemporary generative modeling, claiming state-of-
the-art performance across various domains. Despite their superior sample quality …
the-art performance across various domains. Despite their superior sample quality …
Score-based Diffusion Models via Stochastic Differential Equations--a Technical Tutorial
This is an expository article on the score-based diffusion models, with a particular focus on
the formulation via stochastic differential equations (SDE). After a gentle introduction, we …
the formulation via stochastic differential equations (SDE). After a gentle introduction, we …
Denoising diffusion probabilistic models are optimally adaptive to unknown low dimensionality
The denoising diffusion probabilistic model (DDPM) has emerged as a mainstream
generative model in generative AI. While sharp convergence guarantees have been …
generative model in generative AI. While sharp convergence guarantees have been …