Statistics Seminar: What Are Diffusion Models?
Statistics Seminar: Fall 2026
Speaker: Chen Cheng, Ph.D. Student, Department of Mathematical Sciences, IU Indianapolis.
Talk time: December 1, 2026, 12:15–1:15 p.m. EST
Meeting format: In person in seminar room LD 265, IU Indianapolis.
Presentation overview
Chen Cheng will present an introduction to diffusion models based on Lilian Weng’s tutorial. Diffusion models generate data by learning to reverse a process that gradually adds noise to observed samples. The forward process corrupts the data through a sequence of Gaussian transitions; the learned reverse process starts from noise and progressively reconstructs a sample.
The tutorial develops the probabilistic formulation of denoising diffusion models and the training objective used to learn the reverse transitions. It also connects denoising to score-based generative modeling. The presentation will introduce these foundations and discuss how conditioning and guidance steer generation, along with approaches that reduce the cost of sampling.
Readings
Weng, L. (2021; updated 2024). What are Diffusion Models? Lil’Log. Read online.