2 papers
cs.LG2026
Physics-Aligned Electronic Ground-State Learning Improves Generalization
Eike S. Eberhard, Xaver Kainz, Viktor Kotsev +2
Machine-learned interatomic potentials (MLIPs) excel at in-distribution tasks, accelerating drug and material development, yet they struggle to generalize out-of-distribution. We p…
cs.LG2026
Transferable SCF-Acceleration through Solver-Aligned Initialization Learning
Eike S. Eberhard, Viktor Kotsev, Timm Güthle +1
The cost of Kohn-Sham density functional theory (KS-DFT) calculations scales with the number of solver iterations, which depends on the quality of the initial guess. Machine learni…