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I wrote an interactive article explaining the geometric intuition behind Rectified Flows. I visually explain why flow-models tend to learn curved trajectories, why this is bad for sampling latency, and a relatively simple technique for mitigating it. Check it out! Link 👇

159,395 görüntüleme • 8 ay önce •via X (Twitter)

20 Yorum

Alec Helbling profil fotoğrafı
Alec Helbling8 ay önce

Most of the visualizations have interactive elements that work by running an actual flow model on the front end using Tensorflow.js. It should even work on most mobile devices. Link to blog:

Alec Helbling profil fotoğrafı
Alec Helbling8 ay önce

This project is a part of a broader effort to explain and visualize flow-based generative models with interactive visualization. Check out the code here:

Vaitkus Márton profil fotoğrafı
Vaitkus Márton8 ay önce

Very nice, but IIRC in very high dimensions the paths straighten out quite a lot even with vanilla flow matching, so these 2D examplrs can be a bit misleading for realistic generative models... I even remember some papers that gave some theoretical explanation for this.

Ananya Patelik profil fotoğrafı
Ananya Patelik8 ay önce

love this! curved flows always felt like data taking the scenic route. straightening them shaved 30% off my sampling time. visuals were super clear, thanks!

Sebastian Buzdugan profil fotoğrafı
Sebastian Buzdugan8 ay önce

those curved trajectories always wreck sampling latency

Thirdpen profil fotoğrafı
Thirdpen8 ay önce

sweet 😋

Carmelo schepis profil fotoğrafı
Carmelo schepis8 ay önce

crazy

R profil fotoğrafı
R8 ay önce

Super cool thanks for sharing!

Zorkimer profil fotoğrafı
Zorkimer8 ay önce

I am basically reading this the same way the chimps investigate the obelisk at the start of 2001: A Space Odyssey but it's a beautiful document.

Jason Q.L. Williams profil fotoğrafı
Jason Q.L. Williams8 ay önce

Beautiful, bro

Kelvin 🦖🤓 profil fotoğrafı
Kelvin 🦖🤓8 ay önce

🔥❤️

Coyote profil fotoğrafı
Coyote8 ay önce

What clicked for me is that this isn’t just about faster sampling... it’s about constraint geometry!! Curvature is a symptom of mismatch between learned flow and data manifold. Rectification feels like enforcing the right geometry, not optimizing around the wrong one.

Fabián Souto profil fotoğrafı
Fabián Souto8 ay önce

Pretty awesome work, Alec! Loved how you explained a complex topic in such a simple way. Really good!

Tarandeep Singh profil fotoğrafı
Tarandeep Singh8 ay önce

Cool Stuff, lot of people are so busy trying to keep up with new models and techniques coming out everyday sometimes we forget to actually absorb the material, the true underlying principles underneath.

Saurabh Shukla profil fotoğrafı
Saurabh Shukla8 ay önce

Very cool post, the visualizations are great.

Alec Helbling profil fotoğrafı
Alec Helbling8 ay önce

Thank you!

WaterLyst profil fotoğrafı
WaterLyst7 ay önce

Nice! That sounds super insightful and useful for anyone diving into flow models.#waterlystfeb2

Himanshu Kumar profil fotoğrafı
Himanshu Kumar8 ay önce

@alec_helbling, your explanation of rectified flows will help many understand this complex topic better.

Rahul Raghav profil fotoğrafı
Rahul Raghav8 ay önce

curious how this compares to normalizing flows in other domains

👨‍💻 James Augeri, PhD profil fotoğrafı
👨‍💻 James Augeri, PhD8 ay önce

interesting / arXiv also?

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