%0 Conference Paper %1 fiedler2021practical %A Fiedler, Christian %A Scherer, Carsten W. %A Trimpe, Sebastian %B Proceedings of the AAAI Conference on Artificial Intelligence %C Palo Alto %D 2021 %I Association for the Advancement of Artificial Intelligence %K oa ubs_10008 ubs_20013 ubs_30125 ubs_40314 unibibliografie wos %N 35, 8 %P 7439-7447 %T Practical and Rigorous Uncertainty Bounds for Gaussian Process Regression %U https://ojs.aaai.org/index.php/AAAI/article/view/16912 %@ 978-1-57735-866-4

@inproceedings{fiedler2021practical, added-at = {2022-06-01T11:09:14.000+0200}, address = {Palo Alto}, affiliation = {Fiedler, C (Corresponding Author), Max Planck Inst Intelligent Syst, Intelligent Control Syst Grp, Stuttgart, Germany. Fiedler, C (Corresponding Author), Univ Stuttgart, Math Syst Theory, Stuttgart, Germany. Fiedler, C (Corresponding Author), Rhein Westfal TH Aachen, Inst Data Sci Mech Engn, Aachen, Germany. Fiedler, Christian; Trimpe, Sebastian, Max Planck Inst Intelligent Syst, Intelligent Control Syst Grp, Stuttgart, Germany. Fiedler, Christian; Scherer, Carsten W., Univ Stuttgart, Math Syst Theory, Stuttgart, Germany. Fiedler, Christian; Trimpe, Sebastian, Rhein Westfal TH Aachen, Inst Data Sci Mech Engn, Aachen, Germany.}, author = {Fiedler, Christian and Scherer, Carsten W. and Trimpe, Sebastian}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2e5ebf2c86cd46aa859985423abf8d47c/unibiblio}, booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence}, eventdate = {2021-02-02/2021-02-09}, eventtitle = {35th AAAI Conference on Artificial Intelligence / 33rd Conference on Innovative Applications of Artificial Intelligence / 11th Symposium on Educational Advances in Artificial Intelligence}, interhash = {111705a68e25c07d79e51f7ec762d9ce}, intrahash = {e5ebf2c86cd46aa859985423abf8d47c}, isbn = {978-1-57735-866-4}, keywords = {oa ubs_10008 ubs_20013 ubs_30125 ubs_40314 unibibliografie wos}, language = {eng}, number = {35, 8}, pages = {7439-7447}, publisher = {Association for the Advancement of Artificial Intelligence}, research-areas = {Computer Science; Education & Educational Research}, timestamp = {2022-06-01T09:09:14.000+0200}, title = {Practical and Rigorous Uncertainty Bounds for Gaussian Process Regression}, unique-id = {WOS:000680423507063}, url = {https://ojs.aaai.org/index.php/AAAI/article/view/16912}, venue = {Online}, year = 2021 }