Why can neurons with completely different ion channels fire identically? 🧠

Neuronal degeneracy isn't a bug - it's a feature. Come see how we reconstruct entire degenerate populations from spike times within an interpretable feedback framework.

Poster @dataonbrainmind.bsky.social

#NeurIPS2025 #DBM

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!

At the #ML4PS workshop, @gandry.bsky.social and @sachalewin.bsky.social will present Appa, our large weather model for global data assimilation. Appa differs from other weather models in that it can do reanalysis, nowcasting and forecasting within the same framework. arxiv.org/abs/2504.18720

🚀 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...

Finally released the code for NeuralMPM! 🎉 Mad props to my colleagues @sachalewin.bsky.social and @glouppe.bsky.social

github.com/OmerRochman/...

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

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

<proud advisor>
Hot off the arXiv! 🦬 "Appa: Bending Weather Dynamics with Latent Diffusion Models for Global Data Assimilation" 🌍 Appa is our novel 1.5B-parameter probabilistic weather model that unifies reanalysis, filtering, and forecasting in a single framework. A thread 🧵

"Thank you for submitting your work to arXiv." Time to enjoy the weekend now ☀️

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...

📣 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.

Sharing this again, to cheer up my students after rough #ICLR2025 reviews. We present NeuralMPM, a neural emulation framework for particle-based simulations. Full paper at arxiv.org/abs/2408.15753