{"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/exchangeable-random-measures-for-sparse-and","title":"Exchangeable Random Measures for Sparse and Modular Graphs with Overlapping Communities","arxiv_id":"1602.02114","date":"2016-02-05","proceeding":null,"authors":["Adrien Todeschini","Xenia Miscouridou","François Caron"],"abstract":"We propose a novel statistical model for sparse networks with overlapping\ncommunity structure. The model is based on representing the graph as an\nexchangeable point process, and naturally generalizes existing probabilistic\nmodels with overlapping block-structure to the sparse regime. Our construction\nbuilds on vectors of completely random measures, and has interpretable\nparameters, each node being assigned a vector representing its level of\naffiliation to some latent communities. We develop methods for simulating this\nclass of random graphs, as well as to perform posterior inference. We show that\nthe proposed approach can recover interpretable structure from two real-world\nnetworks and can handle graphs with thousands of nodes and tens of thousands of\nedges.","url_abs":"http://arxiv.org/abs/1602.02114v2","url_pdf":"http://arxiv.org/pdf/1602.02114v2.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":"exchangeable-random-measures-for-sparse-and","repo_url":"https://github.com/misxenia/SNetOC","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}