most citedMachine learning for accuracy in density functional approximations

9 citations · 9 across the 2 of their papers we have counts for

collaborators

2 papers

physics.chem-ph2026

Optimization of random phase approximation calculations for improved energies of molecules, solids, and surfaces

Neung-Kyung Yu, Johannes Voss, Andrew J. Medford

We present an optimized random phase approximation method (optRPA26) that significantly improves upon conventional RPA. The method employs an empirically constructed hybrid functio…

physics.chem-ph2023★ 9 cited

Machine learning for accuracy in density functional approximations

Johannes Voss

Machine learning techniques have found their way into computational chemistry as indispensable tools to accelerate atomistic simulations and materials design. In addition, machine…