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HuMMuS is finally out in Bioinformatics ! 🥳 doi.org/10.1093/bioinf… We provide new insights, notably on HuMMuS robustness, and methylation data contribution in identifying driver TFs. The revision was a very interesting journey, thanks everyone for all the great feedbacks !😊

If you like ResNet and enjoy Optimal Transport, you might enjoy this paper with Raphaël Barboni and F-X Vialard. We show that infinite width/depth ResNet are ("conditional") Wasserstein flows. arxiv.org/abs/2403.12887

There is still time to apply for this postdoc position! If you have a machine learning background and you are interested in applications to genomics/health, do not hesitate to reach out! #postdocall #openposition #recruiting

Are you interested in cis-regulatory DNA interactions? In 2018, #Cicero introduced an algorithm for inferring cis-coaccessible networks from scATAC I’m excited to share #Circe, a Python implementation that is 100x faster and uses 5x less memory! @LauCan88 Julio Saez-Rodriguez 1/5

🚨🚨New ICML 2024 Paper: arxiv.org/abs/2402.05787 How do Transformers perform In-Context Autoregressive Learning? We investigate how causal Transformers learn simple autoregressive processes or order 1. with Raja Giryes 💔, Taiji Suzuki, Mathieu Blondel and Gabriel Peyré 🙏

Come to our #ICML2024 poster presentation tomorrow at 1:30 pm (Poster #903)!

STORIES: Learning cell fate landscapes from spatial transcriptomics using Fused Gromov-Wasserstein biorxiv.org/content/10.110…

🎉 New preprint! biorxiv.org/content/10.110… STORIES learns a differentiation potential from spatial transcriptomics profiled at several time points using Fused Gromov-Wasserstein, an extension of Optimal Transport. Gabriel Peyré @LauCan88

🚨🚨 AI in Bio release 🧬  Very happy to share my work on a Large Cell Model for Gene Network Inference. It is for now just a preprint and more is to come. We are asking the question: “What can 50M cells tell us about gene networks?” ❓Behind it, other questions arose like:

𝗕𝗔𝗖𝗞 𝗧𝗢 𝗕𝗔𝗖𝗞 🥋 L'équipe de France 🇫🇷 de #Judo conserve son titre de champion olympique par équipe mixte 🥇 #JeuxOlympiques | #Paris2024

After a very constructive back and forth with editors and reviewers of Nature Communications, scConfluence has now been published @LauCan88 Gabriel Peyré ! I'll present it this afternoon at the poster session of ECCB2026 Geneva, Switzerland (P296) Published version: nature.com/articles/s4146…

I had the opportunity to present #HuMMuS at ECCB2026 Geneva, Switzerland — amazing experience! Huge thanks to the organisers for their formidable job. 🫶 And special mention for the food and fresh hummus! Perfectly on-point snack reminder 😋🧆

Merci pour l’opportunité d’avoir échangé sur mes recherches et mes expériences ! Merci à mes directeurs de thèse Gabriel Peyré et Rémi Gribonval pour votre supervision 😊

Groundbreaking work, congrats to the team!! 🎉 When I started my PhD 3 years ago, our tabular benchmark showed tree-based models miles ahead of neural networks. On the same benchmark, TabPFN v2 now reaches in 10s what CatBoost achieves in 4h of tuning 🤯

On Tuesday at 2025-02-04 18:00 CET, Jérémie Kalfon will talk about scPrint, a transformer model that infers gene networks from scRNA-seq data, at our 2nd community meeting of 2025! For more information, check out the GitHub: buff.ly/40RJ3gT & pre-print buff.ly/4hwK4Av

I am super happy to annonce that after 9 months under review the first paper of my PhD: scPRINT is finally available on Nature Comms! 🎉🧬 nature.com/articles/s4146…

📡 Join us for the next session in the Foundation Models for Biology Seminar Series (FM4Bio) on May 16 at 10 AM PT, featuring Jérémie Kalfon. Jérémie will introduce scPRINT, a large-scale foundation model trained on 50M single cells from the cellxgene database. The model infers gene