Mixed Continuous and Categorical Flow Matching for 3D De Novo Molecule Generation

Understand

Deep generative models that produce novel molecular structures have the potential to facilitate chemical discovery.

• Diffusion models currently achieve state of the art performance for 3D molecule generation.
• In this work, we explore the use of flow matching, a recently proposed generative modeling framework that generalizes diffusion models, for the task of de novo molecule generation.
• Flow matching provides flexibility in model design; however, the framework is predicated on the assumption of continuously-valued data.