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The BioEmu-1 model and inference code are now public under MIT license!!! Please go ahead, play with it and let us know if there are issues. github.com/microsoft/bioe…

See our preprint on a new computational protein design benchmark!

We made a new, reproducible, fair, (and much harder) motif scaffolding benchmark! With Zhuoqi Zheng, Bo Zhang, Kieran Didi @ICLR Jason Yim Joseph Watson Hai-Feng Chen, Brian L Trippe

Tired of slow diffusion models? Our new paper introduces f-distill, enabling arbitrary f-divergence for one-step diffusion distillation. JS divergence gives SOTA results on text-to-image! Choose the divergence that suits your needs. Joint work with Weili Nie Arash Vahdat 1/N

🔥Excited to present *Proteina* next week (accepted as Oral to ICLR'25) in the ML Protein Engineering Seminar Series. Hear about scalable protein backbone generation, fold class guidance, and more! Also, stay tuned for the upcoming official release, including code and weights!🔥

Our MIT class “6.S184: Introduction to Flow Matching and Diffusion Models” is now available on YouTube! We teach state-of-the-art generative AI algorithms for images, videos, proteins, etc. together with the mathematical tools to understand them. diffusion.csail.mit.edu (1/4)

I really enjoyed seeing how protein generation models scale with more data and weights. Congrats to Nvidia and the core contributors for this amazing work!

Introducing All-atom Diffusion Transformers — towards Foundation Models for generative chemistry, from my internship with the FAIR Chemistry team FAIR Chemistry AI at Meta There are a couple ML ideas which I think are new and exciting in here 👇

Awesome work by Hannnes and Bowen towards improved control of protein structure generation with MultiFlow!

Protein dynamics was the first research to enchant me >10yrs ago, but I left in PhD bc I couldnt find big expt data to evaluate models. Today w Gina El Nesr, I'm thrilled to share the big dynamics data I've been dreaming of, and the mdl we trained: Dyna-1. rb.gy/de5axp

Combining prediction, generation, and modalities (sequence, structure, nucleic acids, small molecules, proteins) is the future. Congrats to the authors! Looking forward to the technical report.

Excited to share our preprint “BoltzDesign1: Inverting All-Atom Structure Prediction Model for Generalized Biomolecular Binder Design” — a collaboration with Martin Pacesa, Zhidian Zhang , Bruno E. Correia, and Sergey Ovchinnikov. 🧬 Code will be released in a couple weeks

New enzymes can unlock chemistry we never had access to before. Here, we introduce RFdiffusion2 (RFD2), a generative model that makes significant strides in de novo enzyme design. Preprint: biorxiv.org/content/10.110… Code: coming soon Animation credit: x.com/ichaydon (1/n)

RFdiffusion => generative binder design. RFdiffusion2 => generative enzyme design. It's rare to find scientists with deep knowledge in chemistry, machine learning, and software engineering like Woody. The complexity of enzymes matches the complexity of his skills. Check out RFD2

I'll be at ICLR. Come check out our generative modeling work! Reach out if you want to chat. Proteina: x.com/karsten_kreis/… Protcomposer: x.com/HannesStaerk/s… Generator matching: x.com/peholderrieth/…

I'll be at the ICLR GEMBio Workshop workshop presenting latent and structure diffusion for protein backbone generation. Come by to talk all things latent for biology. openreview.net/forum?id=Ek7Hs… arxiv.org/abs/2504.09374

Had fun exploring guidance for backbone designability within this latent framework, excited to chat more about guidance with experimental data GEMBio Workshop ICLR

I won't be at ICLR 🥲 but you can talk to these other cool people at my poster, Thursday 3-5:30 PM in Hall 3+2B #10!

#FPIworkshop best paper award goes to Peter Holderrieth Michael Albergo and Tommi Jaakkola. Congrats and great talk Peter!

We've open sourced Adjoint Sampling! It's part of a bundled release showcasing FAIR's research and open source commitment to AI for science. github.com/facebookresear… x.com/AIatMeta/statu…