{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/deep-multi-fidelity-gaussian-processes","title":"Deep Multi-fidelity Gaussian Processes","arxiv_id":"1604.07484","date":"2016-04-26","proceeding":null,"authors":["Maziar Raissi","George Karniadakis"],"abstract":"We develop a novel multi-fidelity framework that goes far beyond the\nclassical AR(1) Co-kriging scheme of Kennedy and O'Hagan (2000). Our method can\nhandle general discontinuous cross-correlations among systems with different\nlevels of fidelity. A combination of multi-fidelity Gaussian Processes (AR(1)\nCo-kriging) and deep neural networks enables us to construct a method that is\nimmune to discontinuities. We demonstrate the effectiveness of the new\ntechnology using standard benchmark problems designed to resemble the outputs\nof complicated high- and low-fidelity codes.","url_abs":"http://arxiv.org/abs/1604.07484v1","url_pdf":"http://arxiv.org/pdf/1604.07484v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"deep-multi-fidelity-gaussian-processes","repo_url":"https://github.com/maziarraissi/TutorialGP","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"gaussian-processes","task_name":"Gaussian Processes"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}