{"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/structure-discovery-in-nonparametric","title":"Structure Discovery in Nonparametric Regression through Compositional Kernel Search","arxiv_id":"1302.4922","date":"2013-02-20","proceeding":null,"authors":["David Duvenaud","James Robert Lloyd","Roger Grosse","Joshua B. Tenenbaum","Zoubin Ghahramani"],"abstract":"Despite its importance, choosing the structural form of the kernel in\nnonparametric regression remains a black art. We define a space of kernel\nstructures which are built compositionally by adding and multiplying a small\nnumber of base kernels. We present a method for searching over this space of\nstructures which mirrors the scientific discovery process. The learned\nstructures can often decompose functions into interpretable components and\nenable long-range extrapolation on time-series datasets. Our structure search\nmethod outperforms many widely used kernels and kernel combination methods on a\nvariety of prediction tasks.","url_abs":"http://arxiv.org/abs/1302.4922v4","url_pdf":"http://arxiv.org/pdf/1302.4922v4.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":"structure-discovery-in-nonparametric","repo_url":"https://github.com/jamesrobertlloyd/gp-structure-search","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"structure-discovery-in-nonparametric","repo_url":"https://github.com/davidar/bib","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"structure-discovery-in-nonparametric","repo_url":"https://github.com/gregoritoo/ABCDflow","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"structure-discovery-in-nonparametric","repo_url":"https://github.com/jamesrobertlloyd/gpss-research","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"structure-discovery-in-nonparametric","repo_url":"https://github.com/sutoiku/autostat","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"time-series-1","task_name":"Time Series"},{"task_slug":"time-series","task_name":"Time Series Analysis"},{"task_slug":"regression-1","task_name":"regression"},{"task_slug":"scientific-discovery","task_name":"scientific discovery"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1302.4922","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}