Statistical Seminar: Every Monday at 2:00 pm.
Time: 2:00 pm – 3:00 pm
Date: 8th December
Place: 3001

 

Sinho CHEWI (Yale University) – Discretization and distribution learning in diffusion models

 

 Abstract: 

 

First, I will review some literature on discretization of diffusion models, focusing on the use of randomized midpoints for deterministic vs. stochastic samplers. Then, I will argue that such sampling guarantees reduce distribution learning, in the form of learning to generate a sample, to score matching. To complement this result, we reduce other forms of distribution learning (parameter estimation and density estimation) to score matching as well. This leads to new consequences for diffusion models, such as asymptotic efficiency of a DDPM-based parameter estimator and algorithms for Gaussian mixture density estimation, as well as to a general approach for establishing cryptographic hardness results for score estimation.

 

 

 

Organizers:

Anna KORBA (CREST), Karim LOUNICI (CMAP) , Jaouad MOURTADA (CREST)

 

 

Sponsors:
CREST-CMAP