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We’ve been excited about discrete flow matching as an alternative to discrete diffusion for biologics design—but how do you scale it to larger vocabularies and control generation? 🌊🌡️Introducing Gumbel-Softmax Flow Matching from our brilliant Sophia Tang! 👇 📜:

What a way to end #ICLR2025 in Singapore 🇸🇬 with an acceptance for PepTune in #ICML2025 in Vancouver 🇨🇦! 🥳 So many congratulations to my brilliant students Sophia Tang and Enol Z.! 🫶 A huge moment for our lab! 🙌 📜: arxiv.org/abs/2412.17780 A quick TLDR for PepTune, if

Most biological processes, like stem cell differentiation, branch into multiple fates, but current trajectory inference methods only predict single paths.🌳To fix this, we introduce BranchSBM 🌿, from our unstoppable Sophia Tang ! 🌟 📜: arxiv.org/abs/2506.09007 💻:

Super excited to introduce "Branched Schrödinger Bridge Matching" (BranchSBM) 🌳, our new framework for learning branched Schrödinger bridge trajectories from a common origin into multiple distinct outcomes! 📄 Preprint: arxiv.org/abs/2506.09007 💻 Code: huggingface.co/ChatterjeeLab/…