21 citations · 27 across the 6 of their papers we have counts for
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cs.LG2025★ 1 cited
Compositional Flows for 3D Molecule and Synthesis Pathway Co-design
Tony Shen, Seonghwan Seo, Ross Irwin +4
Many generative applications, such as synthesis-based 3D molecular design, involve constructing compositional objects with continuous features. Here, we introduce Compositional Gen…
cs.LG2023★ 1 cited
TacoGFN: Target-conditioned GFlowNet for Structure-based Drug Design
Tony Shen, Seonghwan Seo, Grayson Lee +5
Searching the vast chemical space for drug-like molecules that bind with a protein pocket is a challenging task in drug discovery. Recently, structure-based generative models have…
cs.LG2021
Fragment-based molecular generative model with high generalization ability and synthetic accessibility
Seonghwan Seo, Jaechang Lim, Woo Youn Kim
Deep generative models are attracting great attention for molecular design with desired properties. Most existing models generate molecules by sequentially adding atoms. This often…