%0 Journal Article %1 zaverkin2021sampleefficient %A Zaverkin, Viktor %A Holzmüller, David %A Steinwart, Ingo %A Kästner, Johannes %D 2021 %I ACS Publications %J Journal of Chemical Theory and Computation %K mult sent ubs_10003 ubs_10008 ubs_20003 ubs_20013 ubs_30039 ubs_30126 ubs_40065 unibibliografie %N 10 %P 6658-6670 %R 10.1021/acs.jctc.1c00527 %T Fast and Sample-Efficient Interatomic Neural Network Potentials for Molecules and Materials Based on Gaussian Moments %V 17

@article{zaverkin2021sampleefficient, added-at = {2021-12-23T14:18:22.000+0100}, author = {Zaverkin, Viktor and Holzmüller, David and Steinwart, Ingo and Kästner, Johannes}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/216972cc8e03472cd6246198ad7b3c1a6/unibiblio}, doi = {10.1021/acs.jctc.1c00527}, interhash = {ded689e5dca5f542b34bdd372cb59103}, intrahash = {16972cc8e03472cd6246198ad7b3c1a6}, issn = {{1549-9618} and {1549-9626}}, journal = {Journal of Chemical Theory and Computation}, keywords = {mult sent ubs_10003 ubs_10008 ubs_20003 ubs_20013 ubs_30039 ubs_30126 ubs_40065 unibibliografie}, language = {eng}, number = 10, pages = {6658-6670}, publisher = {ACS Publications}, timestamp = {2021-12-23T13:18:22.000+0100}, title = {Fast and Sample-Efficient Interatomic Neural Network Potentials for Molecules and Materials Based on Gaussian Moments}, volume = 17, year = 2021 }