{"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/stochastic-gradient-variational-bayes-for","title":"Stochastic gradient variational Bayes for gamma approximating distributions","arxiv_id":"1509.01631","date":"2015-09-04","proceeding":null,"authors":["David A. Knowles"],"abstract":"While stochastic variational inference is relatively well known for scaling\ninference in Bayesian probabilistic models, related methods also offer ways to\ncircumnavigate the approximation of analytically intractable expectations. The\nkey challenge in either setting is controlling the variance of gradient\nestimates: recent work has shown that for continuous latent variables,\nparticularly multivariate Gaussians, this can be achieved by using the gradient\nof the log posterior. In this paper we apply the same idea to gamma distributed\nlatent variables given gamma variational distributions, enabling\nstraightforward \"black box\" variational inference in models where sparsity and\nnon-negativity are appropriate. We demonstrate the method on a recently\nproposed gamma process model for network data, as well as a novel sparse factor\nanalysis. We outperform generic sampling algorithms and the approach of using\nGaussian variational distributions on transformed variables.","url_abs":"http://arxiv.org/abs/1509.01631v1","url_pdf":"http://arxiv.org/pdf/1509.01631v1.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":"stochastic-gradient-variational-bayes-for","repo_url":"https://github.com/davidaknowles/gamma_sgvb","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"variational-inference","task_name":"Variational Inference"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1509.01631","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}