2 citations · 3 across the 2 of their papers we have counts for
3 papers
All that structure matches does not glitter
Maya M. Martirossyan, Thomas Egg, Philipp Hoellmer +7
Generative models for materials, especially inorganic crystals, hold potential to transform the theoretical prediction of novel compounds and structures. Advancement in this field…
PropMolFlow: Property-Guided Molecule Generation with Geometry-Complete Flow Matching
Cheng Zeng, Jirui Jin, Connor Ambrose +7
Molecule generation is advancing rapidly in chemical discovery and drug design. Flow matching methods have recently set the state of the art (SOTA) in unconditional molecule genera…
Open Materials Generation with Stochastic Interpolants
Philipp Hoellmer, Thomas Egg, Maya M. Martirossyan +11
The discovery of new materials is essential for enabling technological advancements. Computational approaches for predicting novel materials must effectively learn the manifold of…