%0 Journal Article %1 kohlhaas2023gaussian %A Kohlhaas, Rebecca %A Kröker, Ilja %A Oladyshkin, Sergey %A Nowak, Wolfgang %D 2023 %I Springer %J Computational geosciences %K %P 369-389 %R 10.1007/s10596-023-10199-1 %T Gaussian active learning on multi-resolution arbitrary polynomial chaos emulator: concept for bias correction, assessment of surrogate reliability and its application to the carbon dioxide benchmark %V 27

@article{kohlhaas2023gaussian, added-at = {2023-09-29T12:26:31.000+0200}, author = {Kohlhaas, Rebecca and Kröker, Ilja and Oladyshkin, Sergey and Nowak, Wolfgang}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/23c689e0b348a24c6ffc5059266893830/unibiblio}, doi = {10.1007/s10596-023-10199-1}, interhash = {140d70928a099963b5bcf62210a05940}, intrahash = {3c689e0b348a24c6ffc5059266893830}, issn = {1573-1499}, journal = {Computational geosciences}, keywords = {}, language = {eng}, pages = {369-389}, publisher = {Springer}, timestamp = {2023-09-29T10:26:31.000+0200}, title = {Gaussian active learning on multi-resolution arbitrary polynomial chaos emulator: concept for bias correction, assessment of surrogate reliability and its application to the carbon dioxide benchmark}, volume = 27, year = 2023 }