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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 просмотров • 8 месяцев назад •via X (Twitter)

Комментарии: 20

Фото профиля Alec Helbling
Alec Helbling8 месяцев назад

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:

Фото профиля Alec Helbling
Alec Helbling8 месяцев назад

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:

Фото профиля Vaitkus Márton
Vaitkus Márton8 месяцев назад

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.

Фото профиля Ananya Patelik
Ananya Patelik8 месяцев назад

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!

Фото профиля Sebastian Buzdugan
Sebastian Buzdugan8 месяцев назад

those curved trajectories always wreck sampling latency

Фото профиля Thirdpen
Thirdpen8 месяцев назад

sweet 😋

Фото профиля Carmelo schepis
Carmelo schepis8 месяцев назад

crazy

Фото профиля R
R8 месяцев назад

Super cool thanks for sharing!

Фото профиля Zorkimer
Zorkimer8 месяцев назад

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.

Фото профиля Jason Q.L. Williams
Jason Q.L. Williams8 месяцев назад

Beautiful, bro

Фото профиля Kelvin 🦖🤓
Kelvin 🦖🤓8 месяцев назад

🔥❤️

Фото профиля Coyote
Coyote8 месяцев назад

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.

Фото профиля Fabián Souto
Fabián Souto8 месяцев назад

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

Фото профиля Tarandeep Singh
Tarandeep Singh8 месяцев назад

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.

Фото профиля Saurabh Shukla
Saurabh Shukla8 месяцев назад

Very cool post, the visualizations are great.

Фото профиля Alec Helbling
Alec Helbling8 месяцев назад

Thank you!

Фото профиля WaterLyst
WaterLyst7 месяцев назад

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

Фото профиля Himanshu Kumar
Himanshu Kumar8 месяцев назад

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

Фото профиля Rahul Raghav
Rahul Raghav8 месяцев назад

curious how this compares to normalizing flows in other domains

Фото профиля 👨‍💻 James Augeri, PhD
👨‍💻 James Augeri, PhD8 месяцев назад

interesting / arXiv also?

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