[N] MIT Flow Matching and Diffusion Lecture 2026

Peter Holderrieth and Ezra Erives just released their new MIT 2026 course on flow matching and diffusion models! It introduces the full stack of modern AI image, video, protein generators – theory & practice. It includes:

• Lecture Videos: Introducing theory & step-by-step derivations.
• Lecture Notes: Mathematically self-contained.
• Coding: Hands-on exercises for every component.

They improved upon last years’ iteration and added new topics:
Latent spaces, diffusion transformers, building language models with discrete diffusion models.

Everything is available here: https://diffusion.csail.mit.edu

Original tweet by @peholderrieth: https://x.com/peholderrieth/status/2034274122763542953
Lecture notes: https://arxiv.org/abs/2506.02070

Additional resources:

• Flow Matching Guide and Code by Yaron Lipman, Marton Havasi, Peter Holderrieth, et al. https://arxiv.org/pdf/2412.06264
• Reference implementation by Meta https://github.com/facebookresearch/flow_matching