Robin Yadav

Undergraduate Math and CS student @ UBC
Interested in Deep Learning and Optimization

[Robin Yadav @RobinY798]

🎯We further improve diversity/feasibility of generated reactants with Feynman-Kac
(FK) steering, an inference-time steering method
that guides sampling of flow models.
Using a forward-synthesis reward model, we achieve a 19% gain in top-5 round-trip accuracy over prior methods

[Robin Yadav @RobinY798]

Excited to announce RetroSynFlow, a discrete flow matching framework for diverse and accurate retrosynthesis!

📄Paper available here: https://t.co/Z4mgEfdjES

Joint work w/ @qi_yan98 , Guy Wolf, @bose_joey and @lrjconan .

👇 A quick overview 🧵

[Robin Yadav @RobinY798]

🔬We propose the first flow matching framework for retrosynthesis: RetroSynFlow (RSF), which leverages intermediate molecular fragments called synthons.

RSF achieves 60% top-1 accuracy on the USPTO-50k benchmark, outperforming state-of-the-art template-free methods.