Large Language Models (LLMs) - Stanford CME296 Diffusion & Large Vision Models | Spring 2026 | Lecture 1 - Diffusion

Learn more details about this course: https://online.stanford.edu/courses/cme296-diffusion-and-large-vision-models To follow along with the course schedule and syllabus, visit: https://cme296.stanford.edu/syllabus/ Chapters: 00:00:00 Introduction 00:06:04 Class logistics 00:12:23 Outline of the class 00:17:47 Motivating example 00:23:31 Intuition behind diffusion 00:26:33 Image representation 00:46:29 Variational formulation 00:49:01 Joint probability distribution 00:55:58 Strategy to derive a tractable loss 00:57:39 ELBO derivation 01:05:34 KL divergence 01:10:10 Bayes' rule 01:27:18 DDPM training 01:28:11 Inference with DDPM 01:29:49 Faster sampling with DDIM For more information about Stanford’s graduate programs, visit: https://online.stanford.edu/graduate-education Afshine Amidi is an Adjunct Lecturer at Stanford University. Shervine Amidi is an Adjunct Lecturer at Stanford University. View the course playlist: https://www.youtube.com/playlist?list=PLoROMvodv4rNdy8rt2rZ4T2xM0OjADnfu