4 citations · 6 across the 5 of their papers we have counts for
5 papers · 1 filter
Graph Forward Distribution Matching for Molecular Inverse Design
Yihan Zhu, Yuhan Liu, Brett Savoie +2
Achieving precise control over multiple properties without sacrificing chemical validity remains a central challenge in molecular inverse design. Existing reinforcement learning (R…
Controllable Molecular Generative Foundation Models
Yihan Zhu, Yuhan Liu, Weijiang Li +2
Despite the success of foundation models in language and vision, molecular graph generation still lacks a unified framework for heterogeneous design tasks with reliable controllabi…
Open Polymer Challenge: Post-Competition Report
Gang Liu, Sobin Alosious, Subhamoy Mahajan +9
Machine learning (ML) offers a powerful path toward discovering sustainable polymer materials, but progress has been limited by the lack of large, high-quality, and openly accessib…
Graph Diffusion Transformers are In-Context Molecular Designers
Gang Liu, Jie Chen, Yihan Zhu +4
In-context learning allows large models to adapt to new tasks from a few demonstrations, but it has shown limited success in molecular design. Existing databases such as ChEMBL con…
Learning Repetition-Invariant Representations for Polymer Informatics
Yihan Zhu, Gang Liu, Eric Inae +2
Polymers are large macromolecules composed of repeating structural units known as monomers and are widely applied in fields such as energy storage, construction, medicine, and aero…