{"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/gtapprox-surrogate-modeling-for-industrial","title":"GTApprox: surrogate modeling for industrial design","arxiv_id":"1609.01088","date":"2016-09-05","proceeding":null,"authors":["Mikhail Belyaev","Evgeny Burnaev","Ermek Kapushev","Maxim Panov","Pavel Prikhodko","Dmitry Vetrov","Dmitry Yarotsky"],"abstract":"We describe GTApprox - a new tool for medium-scale surrogate modeling in\nindustrial design. Compared to existing software, GTApprox brings several\ninnovations: a few novel approximation algorithms, several advanced methods of\nautomated model selection, novel options in the form of hints. We demonstrate\nthe efficiency of GTApprox on a large collection of test problems. In addition,\nwe describe several applications of GTApprox to real engineering problems.","url_abs":"http://arxiv.org/abs/1609.01088v1","url_pdf":"http://arxiv.org/pdf/1609.01088v1.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":"gtapprox-surrogate-modeling-for-industrial","repo_url":"https://github.com/yarotsky/gtapprox_benchmark","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"model-selection","task_name":"Model Selection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}