🇯🇵Researcher @ Sony AI; 🇹🇼Visiting Asst. Prof. @ Applied Math, NYCU; 🇺🇸PhD @ Math, U. of Minnesota; 🌐https://t.co/hHlwozfDZn
Oct 29 • 9 tweets • 5 min read
Tired to go back to the original papers again and again? Our monograph: a systematic and fundamental recipe you can rely on!
📘 We’re excited to release 《The Principles of Diffusion Models》— with @DrYangSong, @gimdong58085414, @mittu1204, and @StefanoErmon.
It traces the core ideas that shaped diffusion modeling and explains how today’s models work, why they work, and where they’re heading.
🧵You’ll find the link and a few highlights in the thread.
We’d love to hear your thoughts and join some discussions!
⚡ Stay tuned for our markdown version, where you can drop your comments!
🤔What you’ll get from this monograph:
A clear and systematic walkthrough of how diffusion models emerged, how the main formulations connect, and how today’s methods achieve controllability and speed, leading to the next generation of diffusion-based generative models: the flow-map family.
• A unified view linking Variational (VAE), Score-Based (Energy-Based), and Flow-Based (Normalizing Flow) approaches — all as simple changes of variables over time.
• How guidance and numerical solvers make generation faster and controllable.
• The rise of Flow Map Models (e.g., Consistency Model, Consistency Trajectory Model, Mean Flow) shaping the next wave of generative AI.
