We can make population genetics studies more powerful by building priors of variant effect size from features like binding. But we’ve been stuck on linear models! We introduce DeepWAS to learn deep priors on millions of variants! #ICML2025 Andres Potapczynski, @andrewgwils.bsky.social 1/7

There are many domain-specific noise processes for discrete diffusion, but masking dominates! Why? We show masking exploits a key property of discrete diffusion, which we use to unlock the potential of those structured processes and beat masking! w/ Nate Gruver and @andrewgwils.bsky.social 1/7

Thrilled to announce that I am joining DTU in Copenhagen in the fall, as an assistant professor of chemistry. My research group will focus on fundamental methodology in machine learning for molecules.

Want to improve your protein or genomic language model’s performance at zero-shot variant effect prediction? We propose a simple adjustment to likelihood-based predicton

How do you go from a hit in your antibody screen to a suitable drug? Now introducing CloneBO: we optimize antibodies in the lab by teaching a generative model how we optimize them in our bodies! w/ Nat Gruver, Yilun Kuang, Lily Li, @andrewgwils.bsky.social and the team at Big Hat! 1/7

New model trained on new dataset of nearly a million evolving antibody families at AIDrugX workshop Sunday at 4:20 pm (#76) #Neurips! Collab between @andrewgwils.bsky.social and BigHatBio. Stay tuned for full thread on how we used the model to optimize antibodies in the lab in coming days!