Also, I am co-organizing the diffusion workshop with the amazing Valentin De Bortoli Bahjat Kawar Charlotte Bunne James Thornton Chenlin Meng and Jong Chul Ye. We have an amazing line up of speakers, poster, and panel discussion. Stay tuned! diffusionworkshop.github.io

The #NeurIPS2023 Diffusion Model Workshop is just starting - please join us in Hall B1! We look forward to seeing you in person

It happened again! Came to see amazing progress in autonomous driving, but there's only weird math in there.

Supercharge your summer by joining our team at Genentech as an intern! I'll be mentoring one intern focusing on representation learning for omics data. Sounds interesting? Read more and apply here 👉 roche.wd3.myworkdayjobs.com/ROG-A2O-GENE/j…

Join us for the 1st Machine Learning for Genomics Explorations (#MLGenX) workshop at #ICLR2024 on May 11, 2024 in Vienna 🇦🇹! ✨Stay tuned for fantastic keynotes on foundation models, generalizability, and causal methods for genomics! 🗒️Working in this space? Then submit a paper!

Exciting News! The EPFL AI Center is stepping into the social media spotlight for the very first time! Follow us for the latest in AI research, innovation, and community updates. More about the Center📣actu.epfl.ch/news/opening-o… #EPFLAI #EPFLAICenter #FirstTweet #AI4ALL #AIFuture

Cool paper on transition-path sampling with Boltzmann-Generator moves by Michael Plainer, Stephan Günnemann Charlotte Bunne Hannes Stärk: arxiv.org/abs/2312.05340

In a new post with Luca Naef VantAI we ask what is needed for ML to succeed in biological problems and argue that it is necessary to move beyond "white-box data" michael-bronstein.medium.com/the-road-to-bi… w inputs from Nathan Benaich Dominique Beaini @befcorr Georg Winter Patrick Schwab Gevorg Grigoryan

Thrilled to share that my lab is looking for postdocs! In partnership with Chan Zuckerberg Initiative, we're focusing on developing massive biomedical foundation models to create an AI-powered virtual cell. Dream of harnessing the power of 1,000 H100s? Apply now at: snap.stanford.edu/apply/index-po…

Thanks, Andreas Krause, for a great talk yesterday Broad Institute on machine learning in the optimization and discovery loop! ICYMI, we'll share a link to the talk recording soon.

Super excited that our work #CellOT was selected among SIB's Remarkable Outputs 2023🎉: Curious about how we can predict single-cell responses to perturbations? Take a look at our @NatureMethods paper (nature.com/articles/s4159…) and the Research Briefing (nature.com/articles/s4159…)!

How can we integrate two single-cell perturbation screens like Perturb-seq and optical pooled screens? Thrilled to introduce Perturb-OT for cross-modality matching and prediction of perturbation responses! Work with amazing Romain Lopez Charlotte Bunne & Aviv (1/)

We're hiring new faculty at EMBL-EBI - under the great Julio Saez-Rodriguez - we focus on vision and potential and you certainly don't have to be the finished article as a Postdoc (we even hire from last year of PhD) - so - into AI, methods with biological data - apply!

“The paper is a step forward in terms of understanding the heterogeneous response of different cell states to environmental perturbations.” 🥁 #SIBRemarkableOutputs 2023 👏 👉 Find out more about this and the other outputs: tinyurl.com/yca2v9jy #CellOT #MachineLearning

I will give a talk today at 14:20 PDT in #CVPR2024's #CVMI workshop about our work on "Predicting Patient Treatment Outcomes using (Diffusion) Generative Models" and provide a perspective on where the field is moving 💫! Stay tuned! cvmi-workshop.github.io/speakers.html

Statistical optimal transport ift.tt/z4oy1XU

Congratulations to Jayoung Ryu on winning the Best Paper Award at the ICML workshop on AI for Science for her internship work with us at Genentech! We will also be presenting this work next month as part of an oral presentation at MLCB in Vancouver!

3DReact: Geometric Deep Learning for Chemical Reactions pubs.acs.org/doi/10.1021/ac… Puck van Gerwen Ksenia Briling Charlotte Bunne Vignesh Ram Somnath Rubén Laplaza Andreas Krause clemence corminboeuf Ruben NCCR Catalysis NCCR-MARVEL EPFL #JCIM Vol64 Issue15 #MachineLearning #DeepLearning