15 citations · 15 across the 3 of their papers we have counts for
3 papers
physics.chem-ph2024
Transferability of Atom-Based Neural Networks
Frederik Ø. Kjeldal, Janus J. Eriksen
Machine-learning models in chemistry - when based on descriptors of atoms embedded within molecules - face essential challenges in transferring the quality of predictions of local…
physics.chem-ph2023
Properties of Local Electronic Structures
Frederik Ø. Kjeldal, Janus J. Eriksen
The simulation of intrinsic contributions to molecular properties holds the potential to allow for chemistry to be directly inferred from changes to electronic structures at the at…
physics.chem-ph2022★ 15 cited
Decomposing Chemical Space: Applications to the Machine Learning of Atomic Energies
Frederik Ø. Kjeldal, Janus J. Eriksen
We apply a number of atomic decomposition schemes across the standard QM7 dataset -- a small model set of organic molecules at equilibrium geometry -- to inspect the possible emerg…