Lectures related to Exponential Family

Explores Bourgain's theorem on sparsest cut in graphs, emphasizing semimetrics and cut optimization.

Explores diffusion models, focusing on generating samples from a distribution and the importance of denoising in the process.

Covers exponential families and maximum entropy distributions under moment constraints.

Covers the estimation of distributions using samples and probability models.

Covers concentration inequalities and sampling methods for estimating unknown distributions, with a focus on population infection rates.

Explains how entropy measures uncertainty in a system based on possible outcomes.

Covers distributions, derivatives, convergence, and continuity criteria in function spaces.

Covers the concept of property testing using statistical methods.

Covers the estimation of distributions using various methods such as minimum loss and expectation.