{"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/multivar-horner-a-python-package-for","title":"multivar_horner: a python package for computing Horner factorisations of multivariate polynomials","arxiv_id":"2007.13152","date":"2020-07-26","proceeding":null,"authors":["Jannik Michelfeit"],"abstract":"Many applications in the sciences require numerically stable and computationally efficient evaluation of multivariate polynomials. Finding beneficial representations of polynomials, such as Horner factorisations, is therefore crucial. multivar_horner, the python package presented here, is the first open source software for computing multivariate Horner factorisations. This work briefly outlines the functionality of the package and puts it into reference to previous work in the field. Benchmarks additionally prove the advantages of the implementation and Horner factorisations in general.","url_abs":"https://arxiv.org/abs/2007.13152v2","url_pdf":"https://arxiv.org/pdf/2007.13152v2.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":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"multivar-horner-a-python-package-for","repo_url":"https://github.com/MrMinimal64/multivar_horner","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"multivar-horner-a-python-package-for","repo_url":"https://github.com/jannikmi/multivar_horner","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}