Author

Yitong Li

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#machine learning Nov 2025

SynGFN: learning across chemical space with generative flow-based molecular discovery

This study proposes SynGFN, which models molecular design as a cascade of simulated chemical reactions, enabling the assembly of molecules from synthesizable building blocks, as a bridge linking molecular design and synthesis, accelerating exploration and producing diverse, synthesizable, high-performance molecules.

Yuchen Zhu, Shuwang Li, Jihong Chen et al. · Nature Computational Science · 3 citations

#machine learning Open access Jun 2025

HiCLR: Knowledge-Induced Hierarchical Contrastive Learning with Retrosynthesis Prediction Yields a Reaction Foundation Model

HiCLR is the first foundation model that can be broadly applied to various synthesis-related tasks, and it achieves state-of-the-art performance in reaction classification, reaction condition recommendation, reaction yield prediction, synthesis planning, and even molecular property prediction.

Jialu Wu, Yiheng Zhu, Xiaorui Wang et al. · JACS Au · 0 citations