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Jason Yim

@jyim.bsky.social
1.6K followers 378 following 9 posts

PhD candidate at MIT CSAIL. Generative models, protein design. Ex: DeepMind, Microsoft, Instagram, Johns Hopkins University. Website: people.csail.mit.edu/jyim X: x.com/json_yim

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Jason Yim @jyim.bsky.social · 20/04/2025
I'll be at ICLR. Come check out our generative modeling work! Reach out if you want to chat. Proteina: openreview.net/forum?id=TVQ... Protcomposer: openreview.net/forum?id=0ct... Generator matching: openreview.net/forum?id=RuP...
openreview.net
Proteina: Scaling Flow-based Protein Structure Generative Models
Recently, diffusion- and flow-based generative models of protein structures have emerged as a powerful tool for de novo protein design. Here, we develop *Proteina*, a new large-scale flow-based...
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Jason Yim @jyim.bsky.social · 05/03/2025
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!
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Jason Yim @jyim.bsky.social · 19/02/2025
See our preprint on a new computational protein design benchmark!
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Jason Yim @jyim.bsky.social · 13/02/2025
Congrats Simon! I enjoyed our time together while starting protein design at DeepMind. Excited to see what you build. Consider joining latent labs if you're interested in ML and bio!
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Reposted by Jason Yim
Marwin Segler @marwinsegler.bsky.social · 09/12/2024
new preprint on chemical synthesis ML models - showing how to combine multiple models in a principled way - modern Transformers + GNN to featurize chemical reaction: - new insights in where the models shine + bonus: find the quirky named reaction! Feedback welcome! arxiv.org/abs/2412.05269
arxiv.org
Chimera: Accurate retrosynthesis prediction by ensembling models with diverse inductive biases
Planning and conducting chemical syntheses remains a major bottleneck in the discovery of functional small molecules, and prevents fully leveraging generative AI for molecular inverse design. While ea...
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Reposted by Jason Yim
Michael Bronstein @mmbronstein.bsky.social · 09/12/2024
After two years, our paper on generative models for structure-based drug design is finally out in @natcomputsci.bsky.social www.nature.com/articles/s43...
nature.com
Structure-based drug design with equivariant diffusion models - Nature Computational Science
This work applies diffusion models to conditional molecule generation and shows how they can be used to tackle various structure-based drug design problems
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Jason Yim @jyim.bsky.social · 06/12/2024
Excited this is out! I learned a lot interning with Andrew Foong, @franknoe.bsky.social, and the team. Check out Frank's thread and the preprint to learn more.
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Reposted by Jason Yim
Claudio Zeni @claudiozeni.bsky.social · 03/12/2024
🚨Our Machine Learning Force Field Mattersim is now available! 🚨 Check it out here 👇 msft.it/6013oBZLt The force field is designed to be used on a vast range of temperatures and pressures, try it yourself :) Feedback and suggestions are very welcome!
msft.it
GitHub - microsoft/mattersim: MatterSim: A deep learning atomistic model across elements, temperatures and pressures.
MatterSim: A deep learning atomistic model across elements, temperatures and pressures. - microsoft/mattersim
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Reposted by Jason Yim
Sander Dieleman @sedielem.bsky.social · 15/11/2024
In a gratuitous attempt to acquire more followers myself 😁, I've made a start on a "starter pack". Hopefully as more people from 🐦 make it over to 🦋, we can extend this a bit. Suggestions welcome! I've noticed not all accounts seem to be eligible to be added, anyone know what's up with that? 🤔
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