%0 Journal Article %1 bor21 %A Born, Daniel %A Kästner, Johannes %D 2021 %J J. Chem. Theory Comput. %K EXC2075 chemie kaestner kästner pn3 stuttgart theochem theoretische %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 %U https://doi.org/10.1021/acs.jctc.1c00517 %V 17

@article{bor21, added-at = {2021-09-15T08:40:18.000+0200}, author = {Born, Daniel and K\"astner, Johannes}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2f6dfef8de9e25745fda7a0e676ba5443/danielborn}, doi = {10.1021/acs.jctc.1c00517}, interhash = {074bdcdbb4732255005d72e0c9849b48}, intrahash = {f6dfef8de9e25745fda7a0e676ba5443}, journal = {J. Chem. Theory Comput.}, keywords = {EXC2075 chemie kaestner kästner pn3 stuttgart theochem theoretische}, number = 9, pages = {5955-5967}, timestamp = {2021-12-03T11:21:01.000+0100}, title = {Geometry Optimization in Internal Coordinates Based on Gaussian Process Regression: Comparison of Two Approaches}, url = {https://doi.org/10.1021/acs.jctc.1c00517}, volume = 17, year = 2021 }