Stanford CME296 Diffusion & Large Vision Models | Spring 2026 | Lecture 3 - Flow matching
This lecture introduces flow matching as a third paradigm for generative modeling, explaining how it deterministically transports probability distributions from Gaussian noise to data through learned vector fields, while contrasting its velocity-based mechanics with diffusion and score matching approaches.