%0 Journal Article %1 born2021geometry %A Born, Daniel %A Kästner, Johannes %D 2021 %I American Chemical Society %J Journal of chemical theory and computation %K %N 9 %P 5955-5967 %R 10.1021/acs.jctc.1c00517 %T Geometry Optimization in Internal Coordinates Based on Gaussian Process Regression : Comparison of Two Approaches %V 17

@article{born2021geometry, added-at = {2023-08-31T16:21:30.000+0200}, affiliation = {Kastner, J (Corresponding Author), Univ Stuttgart, Inst Theoret Chem, D-70569 Stuttgart, Germany. Born, Daniel; Kaestner, Johannes, Univ Stuttgart, Inst Theoret Chem, D-70569 Stuttgart, Germany.}, author = {Born, Daniel and Kästner, Johannes}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/20489d1406d95943be9bf9e8a941e9097/puma-wartung}, doi = {10.1021/acs.jctc.1c00517}, interhash = {634d44e57dbba9053fe3d83d38f0e50d}, intrahash = {0489d1406d95943be9bf9e8a941e9097}, issn = {{1549-9618} and {1549-9626}}, journal = {Journal of chemical theory and computation}, keywords = {}, language = {eng}, number = 9, orcid-numbers = {Kastner, Johannes/0000-0001-6178-7669}, pages = {5955-5967}, publisher = {American Chemical Society}, research-areas = {Chemistry; Physics}, timestamp = {2023-08-31T14:21:30.000+0200}, title = {Geometry Optimization in Internal Coordinates Based on Gaussian Process Regression : Comparison of Two Approaches}, unique-id = {WOS:000696556000040}, volume = 17, year = 2021 }