20 citations · 24 across the 2 of their papers we have counts for
2 papers
q-bio.QM2021★ 20 cited
Hit and Lead Discovery with Explorative RL and Fragment-based Molecule Generation
Soojung Yang, Doyeong Hwang, Seul Lee +2
Recently, utilizing reinforcement learning (RL) to generate molecules with desired properties has been highlighted as a promising strategy for drug design. A molecular docking prog…
cs.LG2020★ 4 cited
A benchmark study on reliable molecular supervised learning via Bayesian learning
Doyeong Hwang, Grace Lee, Hanseok Jo +2
Virtual screening aims to find desirable compounds from chemical library by using computational methods. For this purpose with machine learning, model outputs that can be interpret…