Deep learning models learn chemistry from less data; fine-tuning on pharma ELN works
marwinsegler · x · 2026-09-22
A research team presented a new deep learning study for chemical reaction prediction with three findings:
- Models can now learn from much less data;
- A new ensemble framework improves robustness;
- Fine-tuning on pharma ELN (electronic lab notebook) data is feasible.
The paper includes extensive analyses, and model code and weights are open-sourced on GitHub—an empirical AI4Science advance for chemistry and drug discovery.
Related event: Microsoft's retroChimera Hits Nature and Goes Open Source(5 posts)→
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