lebellig

I created 3 introductory notebooks on Flow Matching models to help get started with this exciting topic! ✨ 1. Annotated Flow Matching paper: github.com/gle-bellier/... 2. Discrete Flow Matching: github.com/gle-bellier/... 3. Minimal FM in Jax: github.com/gle-bellier/...

POT Python Optimal Transport is 10 years old this week 🎂. Did not think when I pushed the first commit 10 years ago that it would still be here or have this impact (~11M dowloads on PyPI). Open Source Software is a marathon not a sprint. Thanks to all contributors and users (who cite it) 🥳.

Instead of relying on pretrained video latent space we study which tradeoff of spatial and temporal resolution is optimal for real time WM. We open source all our models and training recipes so you can easily adapt it for your needs!

Today my PhD student (for one last day) @orochman.bsky.social is defending his thesis on neural emulators. Check out his latest paper on sampling diffusion models under hard constraints arxiv.org/abs/2601.21033 (NeurIPS 2026)

🚨 New preprint: "Dino Forcing Flow Models: Do not denoise what you can predict" @arrijitghosh.bsky.social @lucasdegeorge.bsky.social P. Couairon, A.A. Efros, @vickykalogeiton.bsky.social and me 📜 arxiv.org/abs/2610.11751 🖥️ arijit-hub.github.io/projects/din... 🤖 github.com/arijit-hub/d... 🧵👇

The 1D heat flow ρ̇=ρ″ reads q̇=q″/(q′)² over quantiles which follow deterministic paths that never cross. www.gpeyre.com/blog/2026/10...

My AI4Sci 2026 keynote on how diffusion models can solve inverse problems in science glouppe.github.io/talk-ai4sci-... featuring several projects from our research group 🤓

Looking for insights into the performance gap between unconditional and conditional diffusion models when the guidance weight is set to 0 👀

New interest: super-resolved images from undertrained flow matching models

I should keep this checkpoint for later

So cool that we have mentats to solve all the difficult math problems we can finally spend our free time fighting across sand deserts under a blazing sun.

Meet Charlotte Pelletier, Assoc. Prof at Université Bretagne Sud 🇫🇷 & ELLIS Member. She researches AI, particularly in the scope of time series analysis with applications in remote sensing and Earth observation. Her advice for young scientists focuses on investing in a strong professional network.

🚀 New paper: Balancing Frequencies and Pixels in Flow Matching We tackle the low-frequency bias in pixel-space flow matching and train JiT up to 40% faster without any architectural changes. 📄 Read it here: arxiv.org/abs/2609.02748

My lab is looking for an Assistant Research Scientist to work on AI for Climate Science. No Ph.D is required for this position, just a BS and relevant experience. The application deadline is Sept 20. Join me in making better climate models! apply.interfolio.com/191796

Yesterday I watched a movie about an AI4Science researcher who gets angry after having his research grant application rejected (badly explained movie plot). Maybe we should take it as a warning about research funding cuts

We are happy to announce that 28 workshops have been accepted for the Paris event, as part of the 102 accepted NeurIPS workshops: blog.neurips.cc/2026/08/10/a... They will take place on Sat Dec 12 + Sun Dec 13, 2026 (for Paris) The suggested deadline for Workshop submissions is close (Aug 29th)!

🌱 Big news from Climate AI Nordics (CAIN)! We are officially registered as an NGO! 🌍✨ Network members can now become official members with AGM voting rights to help shape our future. Join us or get involved! More info: climateainordics.com/news/2026-08-04-cain-ngo/ 🤖💚

Here's the tale of how @jder.bsky.social and I scaled Samudra, a neural ocean emulator capable of predicting 8 years of the ocean on a single GPU, to operate at a full 1/4° resolution (16x the size in bytes). It was quite a humbling process.

NeurIPS submissions confirmed to be a heat-loving species. Warmer year, bigger bloom. Every degree we add, the deadline gets denser 🌻 Good news for the field, we're having a really good growing season 👨‍🌾

You can train your image-to-image flow matching model on badly aligned data, you just have to tell it how bad it is. 🫣 Great work from @lebellig.bsky.social and Aimi Okabayashi with cool applications to remote sensing. It's FlowEO 2.0!

I organize a 1 day workshop on Generative modelling @ENS Lyon, October 9th Call for oral/poster contributions is open; details at gdr-iasis.cnrs.fr/reunions/mod...

I'd like to announce that at @openathena.ai, @jder.bsky.social and I helped @m2lines.bsky.social release Samudra 2. We scaled this neural ocean emulator to train on 16x the size of data in bytes on the same hardware budget. We can now skillfully predict 8 years of the ocean on a single GPU at a 1/4°

Slides for our ICML tutorial on Memorization and Generalization of Diffusion and Flow Matching Models are now available ! 🌀 memorization-generalization.github.io @quentinbertrand.bsky.social

Heading to #ICML2026 🇰🇷 and interested in diffusion models, flow matching, and their generalization capabilities? Don't miss the excellent tutorial by @mathurinmassias.bsky.social and @quentinbertrand.bsky.social on Monday! 📍 Hall D1 🗓️ Monday, July 6 🕘 9:00–11:30 AM Details: icml.cc/virtual/2026...

Heading to #ICML2026 🇰🇷 and interested in diffusion models, flow matching, and their generalization capabilities? Don't miss the excellent tutorial by @mathurinmassias.bsky.social and @quentinbertrand.bsky.social on Monday! 📍 Hall D1 🗓️ Monday, July 6 🕘 9:00–11:30 AM Details: icml.cc/virtual/2026...

🛰️ Introducing UniverSat: one transformer backbone for Earth Observation that handles ANY sensor, ANY spatial, spectral & temporal resolution, ANY scale — with a single set of weights. 🌍

I took Lyon's rainy days in early May as a warm welcome, now with the heatwave I think my acclimatisation is complete, so it's time to make it official! I've started a postdoc on generative models in Inria's Ockham team working with @mathurinmassias.bsky.social and @quentinbertrand.bsky.social ☀️

We explored the impact of variability sources in generative modeling. Turns out, we've been neglecting the error bars associated with training variability all along! We should aim to report results that we are sure of their scientific validity, instead of seed engineering!

one anecdote: I was searching for a link to one of my old papers on Google, and the automated Gemini summary attributed all of my lab's work to my husband

The alpha version of my new book "Optimal Transport for Machine Learners" is out, with in particular an online version with interactive figures www.gpeyre.com/ot4ml/

🎆 New paper! "Random Process Flow Matching: Generative Implicit Representations of Multivariate Random Fields", by Julien Lalanne, accepted to ICML'26 🥳 We're proposing flow-matching for inpainting in ultra-sparse setup, with applications to seismic interpolation. 📜 arxiv.org/abs/2605.28625 1/

"Accept (spotlight)" at ICML'26 😎 Our paper brings particle filters back to life: autoregressive diffusion models + posterior sampling yield optimal proposals for Bayesian filtering, scaling up to GenCast-sized systems. arxiv.org/abs/2605.20028 w/ Thomas Savary and @francois-rozet.bsky.social

Thrilled to share that MIRO is accepted to ICML 2026 @icmlconf.bsky.social ! 🎉 By training on the reward scores, we can simply condition the model on high rewards at inference time to guarantee top-tier, aligned outputs. We’ve updated our paper with some additional results!

📢 The TerraBytes workshop is returning for a 2nd edition - this time at ECCV 2026. Submit your paper before June 18th and join in Malmö, Sweden! 🔗 terrabytes-workshop.github.io

👏 Folks! If you are curious about the Generative Modeling via Drifting paper, but you find it difficult to understand → I wrote a different interpretation of it. It's called: "An Expectation-Maximization interpretation of Generative Modeling via Drifting" davidpicard.github.io/pdf/An_Expec...

My PhD thesis manuscript will be available in the coming months, but I’ve written two blog posts based on the related work chapter: 1. Generative modeling with flow-based models 🪚 2. Data-translation with flow and diffusion bridges 🔨 Open to feedback and discussions! lebellig.github.io/blog/

Want better local models? Want models that are made completely transparently? OpenAthena.ai is hiring on our Marin.community team. We’re especially looking for SWEs and research scientists with experience in data and post training. DM me.

My first blog post in over a year is a deep dive on flow maps🗺️, or how to learn the integral of a diffusion model to enable faster sampling and several other cool tricks. It's the longest one yet👀 Let me know what you think! sander.ai/2026/05/06/f...

My PhD thesis manuscript will be available in the coming months, but I’ve written two blog posts based on the related work chapter: 1. Generative modeling with flow-based models 🪚 2. Data-translation with flow and diffusion bridges 🔨 Open to feedback and discussions! lebellig.github.io/blog/

Delighted to have successfully defended my PhD thesis on "Generative models for Earth Observation, from denoising to domain adaptation" 🪴 This wouldn’t have been possible without the support of my colleagues, my PhD advisor, and my family and friends. Thank you all!

While it is intuitively clear that straighter trajectories should reduce discretization error when integrating an ODE (for instance, in flow matching), I could not find a precise bound. I therefore rewrote the proof of Cauchy-Lipschitz to make this explicit. github.com/gpeyre/Discr...

I wrote a short mathematical companion tutorial to my notebook on discrete diffusion models. It gives an informal derivation of the connection between maximum likelihood estimation of the backward transition kernel and denoising score matching. github.com/gpeyre/Discr...

What if AI could invent enzymes that nature hasn’t seen? 👩‍🔬🧑‍🔬 Introducing 🪩 DISCO: Diffusion for Sequence-structure CO-design 📝 Blog: disco-design.github.io 📄 Paper: arxiv.org/abs/2604.05181 💻 Code: github.com/DISCO-design...

Two research blog posts that look really interesting 👀 "Teaching AI to Invent Enzymes Nature Never Imagined", DISCO: Diffusion for Sequence-structure CO-design disco-design.github.io "How to Generate Text in One Step", Flow Map Language Models one-step-lm.github.io/blog/