2.6k citations · 3.6k across the 16 of their papers we have counts for
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cs.LG2024★ 2 cited
Exploring Discrete Flow Matching for 3D De Novo Molecule Generation
Ian Dunn, David R. Koes
Deep generative models that produce novel molecular structures have the potential to facilitate chemical discovery. Flow matching is a recently proposed generative modeling framewo…
q-bio.BM2024★ 2 cited
Scaling Structure Aware Virtual Screening to Billions of Molecules with SPRINT
Andrew T. McNutt, Abhinav K. Adduri, Caleb N. Ellington +4
Virtual screening of small molecules against protein targets can accelerate drug discovery and development by predicting drug-target interactions (DTIs). However, structure-based m…
q-bio.BM2024★ 1 cited
Mixed Continuous and Categorical Flow Matching for 3D De Novo Molecule Generation
Ian Dunn, David Ryan Koes
Deep generative models that produce novel molecular structures have the potential to facilitate chemical discovery. Diffusion models currently achieve state of the art performance…