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David Pfau @davidpfau.com · 28/01/2025

Remember how, when the lockdowns started, every organization said "we only have two weeks of cash on hand and will shut down if we don't get assistance"? That's basically happening to every single lab and NGO right now, except for no actual reason.

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lebellig @lebellig.bsky.social · 20/01/2025

For the French-speaking audience, S. Mallat's courses at the College de France on Data generation in AI by transport and denoising have just started. I highly recommend them, as I've learned a lot from the overall vision of his courses. Recordings are also available: www.youtube.com/watch?v=5zFh...

youtube.com

Génération de données en IA par transport et débruitage (1) - Stéphane Mallat (2024-2025)

YouTube video by Mathématiques et informatique - Collège de France

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Gabriel Peyré @gabrielpeyre.bsky.social · 15/01/2025

Slides for a general introduction to the use of Optimal Transport methods in learning, with an emphasis on diffusion models, flow matching, training 2 layers neural networks and deep transformers. speakerdeck.com/gpeyre/optim...

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Pierre Alquier @pierrealquier.bsky.social · 05/01/2025

😍😍😍 lmbp.uca.fr/stflour/

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Peyman Milanfar @docmilanfar.bsky.social · 19/12/2024

I'm delighted to note that our paper InDI has been selected as one of two Outstanding Paper awardees by the Transactions on Machine Learning @tmlr-pub.bsky.social We sincerely thank the expert reviewers, Action Editors, the Outstanding Paper Committee, and the Editors for this honor 1/3

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Arnaud Doucet @arnauddoucet.bsky.social · 15/12/2024

The slides of my NeurIPS lecture "From Diffusion Models to Schrödinger Bridges - Generative Modeling meets Optimal Transport" can be found here drive.google.com/file/d/1eLa3...

drive.google.com

BreimanLectureNeurIPS2024_Doucet.pdf

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Alex Thiery @alexxthiery.bsky.social · 14/12/2024

After watching this beautiful keynote by @arnauddoucet.bsky.social , I *had* to give these Schrodinger bridges a try! Very interesting to be able to "straighten" a basic flow-matching approach. Super cool work by @vdebortoli.bsky.social & co-author!

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Surya Ganguli @suryaganguli.bsky.social · 14/12/2024

Speaking at this #NeurIPS2024 workshop on a new analytic theory of creativity in diffusion models that predicts what new images they will create and explains how these images are constructed as patch mosaics of the training data. Great work by @masonkamb.bsky.social scienceofdlworkshop.github.io

scienceofdlworkshop.github.io

SciForDL'24

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Sander Dieleman @sedielem.bsky.social · 14/12/2024

I've been getting a lot of questions about autoregression vs diffusion at #NeurIPS2024 this week! I'm speaking at the adaptive foundation models workshop at 9AM tomorrow (West Hall A), about what happens when we combine modalities and modelling paradigms. adaptive-foundation-models.org

adaptive-foundation-models.org

NeurIPS 2024 Workshop on Adaptive Foundation Models

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Alex Thiery @alexxthiery.bsky.social · 13/12/2024

Fantastic #neurips keynote by Arnaud Doucet! Really like this slide tracing back many of the modern flow-matching / stochastic interpolants ideas to a 1986 result by probabilist Istvan Gyongy describing how to "Markovianize" a diffusion process (eg. having coefficients depending on all the past)

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Valentin De Bortoli @vdebortoli.bsky.social · 13/12/2024

🔥You enjoyed @arnauddoucet.bsky.social talk but want even more Schrodinger Bridge? Come talk to me at our poster! 🔷Schrodinger Bridge Flow for Unpaired Data Translation 🔊 East Exhibit Hall A-C #2504 Work done with my amazing collaborators Ira Korshunova Andriy Mnih and @arnauddoucet.bsky.social

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Sander Dieleman @sedielem.bsky.social · 12/12/2024

When a bunch of diffusers sit down and talk shop, their flow cannot be matched😎 It's time for the #NeurIPS2024 diffusion circle! 🕒Join us at 3PM on Friday December 13. We'll meet near this thing, and venture out from there and find a good spot to sit. Tell your friends!

It's located near the west entrance to the west side of the conference center, on the first floor, in case that helps!

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Anubhav Jain @anubhavj480.bsky.social · 04/12/2024

Have you ever wondered why diffusion models memorize and all initializations lead to the same training sample? As we show, this is because like in dynamic systems, the memorized sample acts as an attractor and a corresponding attraction basin is formed in the denoising trajectory.

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Gabriel Peyré @gabrielpeyre.bsky.social · 04/12/2024

Optimal transport, convolution, and averaging define interpolations between probability distributions. One can find vector fields advecting particles that match these interpolations. They are the Benamou-Brenier, flow-matching, and Dacorogna-Moser fields.

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Gabriel Peyré @gabrielpeyre.bsky.social · 03/12/2024

Hellinger and Wasserstein are the two main geodesic distances on probability distributions. While both minimize the same energy, they differ in their interpolation methods: Hellinger focuses on density, whereas Wasserstein emphasizes position displacements.

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emielhoogeboom.bsky.social @emielhoogeboom.bsky.social · 03/12/2024

This is a really nice blogpost by @RuiqiGao and team that I enjoyed being a part of. My favorite key learnings are: - DDIM sampler == flow matching sampling - (Not) straight? - SD3 weighting (Esser, Rombach, et al) is very similar to the EDM weighting (Karras, et al). 👇

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ruiqigao.bsky.social @ruiqigao.bsky.social · 02/12/2024

A common question nowadays: Which is better, diffusion or flow matching? 🤔 Our answer: They’re two sides of the same coin. We wrote a blog post to show how diffusion models and Gaussian flow matching are equivalent. That’s great: It means you can use them interchangeably.

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Gabriel Peyré @gabrielpeyre.bsky.social · 30/11/2024

I wrote a summary of the main ingredients of the neat proof by Hugo Lavenant that diffusion models do not generally define optimal transport. github.com/mathematical...

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Gabriele Corso @gcorso.bsky.social · 17/11/2024

Thrilled to announce Boltz-1, the first open-source and commercially available model to achieve AlphaFold3-level accuracy on biomolecular structure prediction! An exciting collaboration with Jeremy, Saro, and an amazing team at MIT and Genesis Therapeutics. A thread!

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