{"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/learning-non-parametric-markov-networks-with","title":"Learning non-parametric Markov networks with mutual information","arxiv_id":"1708.02497","date":"2017-08-08","proceeding":null,"authors":["Janne Leppä-aho","Santeri Räisänen","Xiao Yang","Teemu Roos"],"abstract":"We propose a method for learning Markov network structures for continuous\ndata without invoking any assumptions about the distribution of the variables.\nThe method makes use of previous work on a non-parametric estimator for mutual\ninformation which is used to create a non-parametric test for multivariate\nconditional independence. This independence test is then combined with an\nefficient constraint-based algorithm for learning the graph structure. The\nperformance of the method is evaluated on several synthetic data sets and it is\nshown to learn considerably more accurate structures than competing methods\nwhen the dependencies between the variables involve non-linearities.","url_abs":"http://arxiv.org/abs/1708.02497v1","url_pdf":"http://arxiv.org/pdf/1708.02497v1.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":"learning-non-parametric-markov-networks-with","repo_url":"https://github.com/janlepppa/graph_learn_mi","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}