Marwin Segler
Microsoft Research (United Kingdom)(GB)
Publications by Year
Research Areas
Machine Learning in Materials Science, Computational Drug Discovery Methods, Protein Structure and Dynamics, Chemical Synthesis and Analysis, Catalytic C–H Functionalization Methods
Most-Cited Works
- → Opportunities and obstacles for deep learning in biology and medicine(2018)2,170 cited
- → Planning chemical syntheses with deep neural networks and symbolic AI(2018)1,862 cited
- → Generating Focused Molecule Libraries for Drug Discovery with Recurrent Neural Networks(2017)1,636 cited
- → Neural‐Symbolic Machine Learning for Retrosynthesis and Reaction Prediction(2017)608 cited
- → Artificial intelligence for natural product drug discovery(2023)342 cited
- → Machine learning the ropes: principles, applications and directions in synthetic chemistry(2020)267 cited
- → Artificial Intelligence in Drug Discovery(2018)170 cited
- → Evaluation guidelines for machine learning tools in the chemical sciences(2022)142 cited
- → Molecular representation learning with language models and domain-relevant auxiliary tasks(2020)113 cited