9 citations · 9 across the 2 of their papers we have counts for
2 papers
cs.LG2023
The power of motifs as inductive bias for learning molecular distributions
Johanna Sommer, Leon Hetzel, David Lüdke +2
Machine learning for molecules holds great potential for efficiently exploring the vast chemical space and thus streamlining the drug discovery process by facilitating the design o…
physics.flu-dyn2023★ 9 cited
From Zero to Turbulence: Generative Modeling for 3D Flow Simulation
Marten Lienen, David Lüdke, Jan Hansen-Palmus +1
Simulations of turbulent flows in 3D are one of the most expensive simulations in computational fluid dynamics (CFD). Many works have been written on surrogate models to replace nu…