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
00:00:55 Recap of last episodes
00:06:58 Problem formulation
00:10:53 Trajectory
00:11:54 Flow
00:13:59 Probability path
00:15:05 Vector field
00:18:42 Ordinary differential equation
00:23:51 Continuity equation
00:36:34 Micro and macro perspectives
00:41:15 Flow models
00:43:01 Continuous normalizing flows
00:46:16 Flow matching
00:47:58 Conditional probability path and vector field
01:01:10 Marginal probability path and vector field
01:10:54 Conditional flow matching
01:26:02 Why not velocity matching
01:28:50 Training
01:29:55 Inference
01:30:31 Rectified flow
01:43:05 Links with diffusion and score matching
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