3 papers
physics.chem-ph2025
Transfer learning of GW-Bethe-Salpeter Equation excitation energies
Dario Baum, Arno Förster, Lucas Visscher
A persistent challenge in machine learning for electronic-structure calculations is the sharp imbalance between abundant low-fidelity data like DFT or TDDFT results and the scarcit…
physics.chem-ph2025
qs quasiparticle and -BSE excitation energies of 133,885 molecules
Dario Baum, Arno Förster, Lucas Visscher
Machine learning applications in the chemical sciences, especially when based on neural networks, critically depend on the availability of large quantities of high quality data. As…
physics.chem-ph2025
Predicting complete basis set limit quasiparticle energies from triple- calculations
Dario Baum, Lucas Visscher, Arno Förster
We present a simple linear model to estimate the basis set incompleteness errors (BSIE) of (vertex-corrected) QP energies based on the kinetic energy of the corresponding orbi…