activity
20232026
most citedInput convex neural networks: universal approximation theorem and implementation for isotropic polyconvex hyperelastic energies

10 citations · 10 across the 5 of their papers we have counts for

collaborators
Showing 2023Show all

1 paper · 1 filter

cs.CE2023

Incorporating sufficient physical information into artificial neural networks: a guaranteed improvement via physics-based Rao-Blackwellization

Gian-Luca Geuken, Jörn Mosler, Patrick Kurzeja

The concept of Rao-Blackwellization is employed to improve predictions of artificial neural networks by physical information. The error norm and the proof of improvement are transf…