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
00:04:33 Motivation behind score matching
00:14:30 Lanvegin sampling
00:18:43 Score estimation
00:19:50 Implicit score matching, sliced score matching
00:20:56 Score of a Gaussian distribution
00:29:58 Denoising score matching
00:40:44 Limitations of DSM
00:49:49 Noise conditional score networks
00:52:49 Annealed Langevin dynamics
00:58:09 Parallel between DDPM and score
01:04:37 Continuous derivation
01:14:31 SDE formulation
01:22:54 Training
01:24:29 Reverse SDE
01:28:46 Inference with Euler-Maruyama
01:30:32 PF-ODE
01:41:24 DPM-Solver
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