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I finally released my new video on YouTube about Diffusion Models / Score-Based Generative Models. Literally planned this for a year and put so much work in. I think this approach to diffusion models is so intuitive and highly recommend giving that a go! Video is 38min long, so...

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dome | Outlier

3,060 subscribers

54,560 просмотров • 1 год назад •via X (Twitter)

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Комментарии: 10

Фото профиля 1LittleCoder💻
1LittleCoder💻1 год назад

That's a crazy timeline. Respect!

Фото профиля dome | Outlier
dome | Outlier1 год назад

Thank you haha

Фото профиля Robin Rombach
Robin Rombach1 год назад

Nice, richtig gut 😍

Фото профиля dome | Outlier
dome | Outlier1 год назад

Nächstes video dann über Flow Matching. Ich werd auf dich zurückkommen mit paar Fragen :c

Фото профиля Ryan Tabrizi
Ryan Tabrizi1 год назад

Learned a lot following your derivations. Thanks!

Фото профиля dome | Outlier
dome | Outlier1 год назад

So awesome to hear. One small addition, the solution to this is not just Sliced Score Matching. It‘s what Pascal Vincent came up with when he combined Score Matching & Denoising Autoencoders -> Denoising Score Matching So basically two solutions to this problem, and mostly DSM is used :) Super happy the video was helpful

Фото профиля Ariel N. Lee
Ariel N. Lee1 год назад

This is awesome

Фото профиля Ashutosh Narang
Ashutosh Narang1 год назад

@jeremyphoward Watching it today, thank you

Фото профиля The Variational Book
The Variational Book1 год назад

@dome_271 looks great, what did you use to make the video? Seems like would be right up your alley

Фото профиля dome | Outlier
dome | Outlier1 год назад

Manim and Premiere Pro :c

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Diffusion clicked for me when I read about score-based models, a line of work pioneered by Stefano Ermon (et al.) at Stanford. So it was a full-circle moment to collab with him and Inception on a video about training & sampling techniques for making diffusion LLMs faster.
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Diffusion clicked for me when I read about score-based models, a line of work pioneered by Stefano Ermon (et al.) at Stanford. So it was a full-circle moment to collab with him and Inception on a video about training & sampling techniques for making diffusion LLMs faster.

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Dreamix: Video Diffusion Models are General Video Editors abs: project page: present diffusion-based method that is able to perform text-based motion and appearance editing of general videos

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Announcing Diffusion Forcing Transformer (DFoT), our new video diffusion algorithm that generates ultra-long videos of 800+ frames. DFoT enables History Guidance, a simple add-on to any existing video diffusion models for a quality boost. Website: (1/7)

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This is the first time in a long while that I’ve let myself think about this again and rewatch this video since the first time. It hurt so much I could barely handle it…. Thank you so much Seungkwan and 17, i love you guys so much
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This is the first time in a long while that I’ve let myself think about this again and rewatch this video since the first time. It hurt so much I could barely handle it…. Thank you so much Seungkwan and 17, i love you guys so much

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32,888 просмотров • 2 лет назад

working towards action-conditioned video diffusion models for now this is just cs2 gameplay, and i parse the keypresses from the .dem game file next steps will be to work on a scalable data loader then coding the model
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working towards action-conditioned video diffusion models for now this is just cs2 gameplay, and i parse the keypresses from the .dem game file next steps will be to work on a scalable data loader then coding the model

Arnie Ramesh

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Excited to share our interview with Sander Dieleman! This is Part 3 in our History of Diffusion series. We talk about diffusion as spectral autoregression, diffusion language models, flow matching, and much more. Enjoy!

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Synthesizing worlds with video diffusion models is often inconsistent — moving the camera back and forth leads to different scenes. We propose 🌐𝗪𝗼𝗿𝗹𝗱𝗠𝗲𝗺, a memory-based approach that ensures consistent world simulation without relying on explicit 3D reconstruction.

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Ill Try to make a model pack of the npcs soon, since the models uses layered masks I will need to make some custom textures that I will add with the material info so people can use the models better, so for those who want models I will ask patience n.n
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Ill Try to make a model pack of the npcs soon, since the models uses layered masks I will need to make some custom textures that I will add with the material info so people can use the models better, so for those who want models I will ask patience n.n

ChicoEevee

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Took some time off but I’m excited to be back and find out that we reached 3k!!! I’m so happy for that thank you so so much for this 🥰🥰🥰 (a video that I took on my little vacation😜)

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My craft is so different, even my biggest inspirations and role models don’t even know where to put me as I respectfully say that. It’s a gift and a curse.
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I highly recommend Tesla investors watch this video. First time I go directly to video in my research since I had to cover too much context.

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Been thinking about what this paper really means. "Video diffusion" and "World Models" are becoming synonymous. Neural Computers are basically video diffusion world models for terminal envs and GUI. Lots of talk last week about automating Manim videos. In theory, we should be able to train these world models on a 10000 hours of diverse manim videos and "see where it goes" If a NC can generate outputs to terminal commands, it should be able to generate videos like this directly from prompt too. Without writing code.

AVB

119,949 просмотров • 2 месяцев назад