Extrapolative Bayesian Optimization with Gaussian Process and Neural Network Ensemble Surrogate Models

Advanced Intelligent SystemsVolume 3, Issue 11 2170077 FrontispieceOpen Access Extrapolative Bayesian Optimization with Gaussian Process and Neural Network Ensemble Surrogate Models Yee-Fun Lim, Corresponding Author Yee-Fun Lim limyf@imre.a-star.edu.sg orcid.org/0000-0001-8276-2364 Institute of Materials Research and Engineering, A*STAR (Agency for Science Technology and Research), 2 Fusionopolis Way, #08-03 Innovis, Singapore, 138634 Republic of SingaporeSearch for more papers by this authorChee Koon Ng, Chee Koon Ng orcid.org/0000-0003-2044-5296 Institute of Materials Research and Engineering, A*STAR (Agency for Science Technology and Research), 2 Fusionopolis Way, #08-03 Innovis, Singapore, 138634 Republic of SingaporeSearch for more papers by this authorU.S. Vaitesswar, U.S. Vaitesswar Department of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798 Republic of SingaporeSearch for more papers by this authorKedar Hippalgaonkar, Corresponding Author Kedar Hippalgaonkar kedar@ntu.edu.sg orcid.org/0000-0002-1270-9047 Institute of Materials Research and Engineering, A*STAR (Agency for Science Technology and Research), 2 Fusionopolis Way, #08-03 Innovis, Singapore, 138634 Republic of Singapore Department of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798 Republic of SingaporeSearch for more papers by this author Yee-Fun Lim, Corresponding Author Yee-Fun Lim limyf@imre.a-star.edu.sg orcid.org/0000-0001-8276-2364 Institute of Materials Research and Engineering, A*STAR (Agency for Science Technology and Research), 2 Fusionopolis Way, #08-03 Innovis, Singapore, 138634 Republic of SingaporeSearch for more papers by this authorChee Koon Ng, Chee Koon Ng orcid.org/0000-0003-2044-5296 Institute of Materials Research and Engineering, A*STAR (Agency for Science Technology and Research), 2 Fusionopolis Way, #08-03 Innovis, Singapore, 138634 Republic of SingaporeSearch for more papers by this authorU.S. Vaitesswar, U.S. Vaitesswar Department of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798 Republic of SingaporeSearch for more papers by this authorKedar Hippalgaonkar, Corresponding Author Kedar Hippalgaonkar kedar@ntu.edu.sg orcid.org/0000-0002-1270-9047 Institute of Materials Research and Engineering, A*STAR (Agency for Science Technology and Research), 2 Fusionopolis Way, #08-03 Innovis, Singapore, 138634 Republic of Singapore Department of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798 Republic of SingaporeSearch for more papers by this author First published: 22 November 2021 https://doi.org/10.1002/aisy.202170077AboutPDF ToolsExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Abstract Bayesian Optimization 3D visualization of Gaussian process (GP) prediction and uncertainty manifolds for a concrete compressive strength dataset, which evolved after several iterations of Bayesian optimization with a GP surrogate model. More details can be found in article 2100101 by Yee-Fun Lim, Kedar Hippalgaonkar and co-workers. Volume3, Issue11November 20212170077 RelatedInformation