226 citations · 236 across the 9 of their papers we have counts for
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cs.LG2020
Visualizing Deep Graph Generative Models for Drug Discovery
Karan Yang, Chengxi Zang, Fei Wang
Drug discovery aims at designing novel molecules with specific desired properties for clinical trials. Over past decades, drug discovery and development have been a costly and time…
stat.ML2020★ 226 cited
MoFlow: An Invertible Flow Model for Generating Molecular Graphs
Chengxi Zang, Fei Wang
Generating molecular graphs with desired chemical properties driven by deep graph generative models provides a very promising way to accelerate drug discovery process. Such graph g…