Machine Learning

1 readers

1 users here now

Community Rules:

Be nice. No offensive behavior, insults or attacks: we encourage a diverse community in which members feel safe and have a voice.
Make your post clear and comprehensive: posts that lack insight or effort will be removed. (ex: questions which are easily googled)
Beginner or career related questions go elsewhere. This community is focused in discussion of research and new projects that advance the state-of-the-art.
Limit self-promotion. Comments and posts should be first and foremost about topics of interest to ML observers and practitioners. Limited self-promotion is tolerated, but the sub is not here as merely a source for free advertisement. Such posts will be removed at the discretion of the mods.

founded 10 months ago

MODERATORS

communick@academy.garden

[R] Beyond U: Making Diffusion Models Faster & Lighter (alien.top)

submitted 10 months ago by APaperADay@alien.top to c/machinelearning@academy.garden

5 comments fedilink hide all child comments

Paper: https://arxiv.org/abs/2310.20092

Abstract:

Diffusion models are a family of generative models that yield record-breaking performance in tasks such as image synthesis, video generation, and molecule design. Despite their capabilities, their efficiency, especially in the reverse denoising process, remains a challenge due to slow convergence rates and high computational costs. In this work, we introduce an approach that leverages continuous dynamical systems to design a novel denoising network for diffusion models that is more parameter-efficient, exhibits faster convergence, and demonstrates increased noise robustness. Experimenting with denoising probabilistic diffusion models, our framework operates with approximately a quarter of the parameters and 30% of the Floating Point Operations (FLOPs) compared to standard U-Nets in Denoising Diffusion Probabilistic Models (DDPMs). Furthermore, our model is up to 70% faster in inference than the baseline models when measured in equal conditions while converging to better quality solutions.

https://preview.redd.it/djk9mdlc9e0c1.png?width=995&format=png&auto=webp&s=65a002f1f320e68b71753ac32c6386c22e76c1c9

https://preview.redd.it/i87gizkc9e0c1.png?width=1108&format=png&auto=webp&s=34f25ecc319ffa34f545e850a5c95cb007e0abd8

you are viewing a single comment's thread
view the rest of the comments

[–] CatalyzeX_code_bot@alien.top 1 points 10 months ago

No relevant code picked up just yet for "Beyond U: Making Diffusion Models Faster & Lighter".

Request code from the authors or ask a question.

If you have code to share with the community, please add it here 😊🙏

To opt out from receiving code links, DM me.