{"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/the-population-posterior-and-bayesian","title":"The Population Posterior and Bayesian Inference on Streams","arxiv_id":"1507.05253","date":"2015-07-19","proceeding":null,"authors":["James McInerney","Rajesh Ranganath","David M. Blei"],"abstract":"Many modern data analysis problems involve inferences from streaming data.\nHowever, streaming data is not easily amenable to the standard probabilistic\nmodeling approaches, which assume that we condition on finite data. We develop\npopulation variational Bayes, a new approach for using Bayesian modeling to\nanalyze streams of data. It approximates a new type of distribution, the\npopulation posterior, which combines the notion of a population distribution of\nthe data with Bayesian inference in a probabilistic model. We study our method\nwith latent Dirichlet allocation and Dirichlet process mixtures on several\nlarge-scale data sets.","url_abs":"http://arxiv.org/abs/1507.05253v2","url_pdf":"http://arxiv.org/pdf/1507.05253v2.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":"the-population-posterior-and-bayesian","repo_url":"https://github.com/bachtranxuan/GCTM","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"the-population-posterior-and-bayesian","repo_url":"https://github.com/bachtranxuan/TPS","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"bayesian-inference","task_name":"Bayesian Inference"}],"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}