Gérôme Andry @Neurips2025

We did 😇

If you are interested in diffusion models for dynamical systems and posterior inference, stop by our poster at ML4PS workshop (@neuripsconf.bsky.social) at 11am!

Come and see how we apply modern methods to the challenging field of global weather inference!

Beautiful keynote by @gaelvaroquaux.bsky.social at @euripsconf.bsky.social .

Feel free to reach out at the conference for discussing about diffusion models, posterior inference and dynamical systems 😇

Our Montefiore Science with AI lab will be at #NeurIPS2025 presenting 1 paper at the main conference and 3 papers at workshops. If you are attending, feel free to reach out with the crew to discuss science, AI, or just to say hi! (I won't attend this year unfortunately 🌱)

montefiore-sail/appa · Datasets at Hugging Face We’re on a journey to advance and democratize artificial intelligence through open source and open science.

Special shoutout to @sachalewin.bsky.social for a huge code refactor + super clean GitHub 𝐰𝐢𝐤𝐢.
👉 Explore the repo, try Appa (weights on Hugging Face huggingface.co/datasets/mon...), and let us know what you think!

Big thanks to everyone who made this possible 🙏 @sachalewin.bsky.social, @francois-rozet.bsky.social, @orochman.bsky.social, Victor Mangeleer @mapirlet.bsky.social, Elise Faulx, Marilaure Grégoire and our promoter @glouppe.bsky.social for his tremendous support.

Next stop: 𝐒𝐚𝐧 𝐃𝐢𝐞𝐠𝐨! ✈️
We’ll present Appa at the workshop and continue improving:
• Incorporating real observations
• Reducing temporal error growth
… and we’d love your suggestions or feedback!

We believe Appa carries important messages. 🌍
How to flexibly incorporate observations to tackle diverse assimilation tasks in a 𝐮𝐧𝐢𝐟𝐢𝐞𝐝 𝐟𝐫𝐚𝐦𝐞𝐰𝐨𝐫𝐤? What are the advantages of compressing data for inference at this scale? And what are the limitations?

Appa: Bending Weather Dynamics with Latent Diffusion Models for Global Data Assimilation Deep learning has transformed weather forecasting by improving both its accuracy and computational efficiency. However, before any forecast can begin, weather centers must identify the current atmosph...

This release builds on our recently submitted ML4PS @ NeurIPS workshop paper, and already goes beyond the first arXiv version (April 2025, arxiv.org/abs/2504.18720).
Appa now uses a simpler architecture and still reaches strong performance with ~𝟓𝟑𝟎× 𝐜𝐨𝐦𝐩𝐫𝐞𝐬𝐬𝐢𝐨𝐧!

GitHub - montefiore-sail/appa: Code for the publication "Appa: Bending Weather Dynamics with Latent Diffusion Models for Global Data Assimilation". Code for the publication "Appa: Bending Weather Dynamics with Latent Diffusion Models for Global Data Assimilation". - montefiore-sail/appa

🚀 After more than a year of work — and many great discussions with curious minds & domain experts — we’re excited to announce the public release of 𝐀𝐩𝐩𝐚, our latent diffusion model for global data assimilation!

Check the repo and the complete wiki!
github.com/montefiore-s...

Positions remain open! Both PhD and postdoctoral opportunities are available on scientific foundation models. An additional position is also available on AI for regional climate models (jointly with @xavierfettweis.bsky.social). Do not hesitate to apply!

📢 I am looking for AI post-doc/research/engineer positions in Europe (Paris, London, Zurich, ...) starting 2026. My work revolves around generative modeling and AI for Science, with 4+ publications at top conferences during my PhD. If you are hiring, please reach out! If not, please repost 🔁

Andry, Rozet, Lewin, Rochman, Mangeleer, Pirlet, Faulx, Gr\'egoire, Louppe: Appa: Bending Weather Dynamics with Latent Diffusion Models for Global Data Assimilation https://arxiv.org/abs/2504.18720 https://arxiv.org/pdf/2504.18720 https://arxiv.org/html/2504.18720

Kudos again @sachalewin.bsky.social for the visualizations!

montefiore-sail.github.io/appa/

Appa: Bending Weather Dynamics with Latent Diffusion Models for Global Data Assimilation Deep learning has transformed weather forecasting by improving both its accuracy and computational efficiency. However, before any forecast can begin, weather centers must identify the current atmosph...

arxiv.org/abs/2504.18720

After several month, our work is out! 🦬

Look at our new paper with the team!

Thanks to all of them!!

@glouppe.bsky.social
@sachalewin.bsky.social
@francois-rozet.bsky.social
@orochman.bsky.social
@mapirlet.bsky.social
Victor Mangeleer
Elise Faulx

Let's start this workshop @ecmwf.int about data assimilation! 🌍

🔥 Azula 0.3.0 is out with many new features, including new super fast samplers (LMS, DPM-Solver), new guidance methods (DPS, MMPS) and new plugins (VDM, EMD, EMD2). Check it out!

Now accepted at @tmlr-pub.bsky.social 🥳

What channels would you recommend for sharing PhD/post-doc position offers? The theme is foundation models for the physical sciences, with weather as a specific target.

📣 Hiring! I am looking for PhD/postdoc candidates to work on foundation models for science at @ULiege, with a special focus on weather and climate systems. 🌏 Three positions are open around deep learning, physics-informed FMs and inverse problems with FMs.

I can't breath anymore but it was so nice!

So much work """just""" for an autoencoder... 🤯😵

Exploring data assimilation with score-based models—and as a bonus, I know what a Markov blanket is!

Score-based Data Assimilation by @francois-rozet.bsky.social and @glouppe.bsky.social

I'm interested too 🤓

Whoops 😅