{"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/sum-product-graphical-models","title":"Sum-Product Graphical Models","arxiv_id":"1708.06438","date":"2017-08-21","proceeding":null,"authors":["Mattia Desana","Christoph Schnörr"],"abstract":"This paper introduces a new probabilistic architecture called Sum-Product\nGraphical Model (SPGM). SPGMs combine traits from Sum-Product Networks (SPNs)\nand Graphical Models (GMs): Like SPNs, SPGMs always enable tractable inference\nusing a class of models that incorporate context specific independence. Like\nGMs, SPGMs provide a high-level model interpretation in terms of conditional\nindependence assumptions and corresponding factorizations. Thus, the new\narchitecture represents a class of probability distributions that combines, for\nthe first time, the semantics of graphical models with the evaluation\nefficiency of SPNs. We also propose a novel algorithm for learning both the\nstructure and the parameters of SPGMs. A comparative empirical evaluation\ndemonstrates competitive performances of our approach in density estimation.","url_abs":"http://arxiv.org/abs/1708.06438v1","url_pdf":"http://arxiv.org/pdf/1708.06438v1.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":"sum-product-graphical-models","repo_url":"https://github.com/ocarinamat/SumProductGraphMod","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"density-estimation","task_name":"Density Estimation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}