825 citations · 978 across the 6 of their papers we have counts for
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physics.chem-ph2020★ 27 cited
Generating 3D Molecular Structures Conditional on a Receptor Binding Site with Deep Generative Models
Tomohide Masuda, Matthew Ragoza, David Ryan Koes
Deep generative models have been applied with increasing success to the generation of two dimensional molecules as SMILES strings and molecular graphs. In this work we describe for…
q-bio.QM2020★ 11 cited
Learning a Continuous Representation of 3D Molecular Structures with Deep Generative Models
Matthew Ragoza, Tomohide Masuda, David Ryan Koes
Machine learning in drug discovery has been focused on virtual screening of molecular libraries using discriminative models. Generative models are an entirely different approach th…