3 papers
cs.LG2026
Surrogate Functionals for Machine-Learned Orbital-Free Density Functional Theory
Roman Remme, Fred A. Hamprecht
We introduce surrogate functionals: machine-learned energy functionals for orbital-free density functional theory (OF-DFT) which are defined not by universal fidelity to a physical…
physics.chem-ph2025
Stable and Accurate Orbital-Free DFT Powered by Machine Learning
Roman Remme, Tobias Kaczun, Tim Ebert +10
Hohenberg and Kohn have proven that the electronic energy and the one-particle electron density can, in principle, be obtained by minimizing an energy functional with respect to th…
cs.LG2025
Beyond Canonicalization: How Tensorial Messages Improve Equivariant Message Passing
Peter Lippmann, Gerrit Gerhartz, Roman Remme +1
In numerous applications of geometric deep learning, the studied systems exhibit spatial symmetries and it is desirable to enforce these. For the symmetry of global rotations and r…