{"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/zhusuan-a-library-for-bayesian-deep-learning","title":"ZhuSuan: A Library for Bayesian Deep Learning","arxiv_id":"1709.05870","date":"2017-09-18","proceeding":null,"authors":["Jiaxin Shi","Jianfei Chen","Jun Zhu","Shengyang Sun","Yucen Luo","Yihong Gu","Yuhao Zhou"],"abstract":"In this paper we introduce ZhuSuan, a python probabilistic programming\nlibrary for Bayesian deep learning, which conjoins the complimentary advantages\nof Bayesian methods and deep learning. ZhuSuan is built upon Tensorflow. Unlike\nexisting deep learning libraries, which are mainly designed for deterministic\nneural networks and supervised tasks, ZhuSuan is featured for its deep root\ninto Bayesian inference, thus supporting various kinds of probabilistic models,\nincluding both the traditional hierarchical Bayesian models and recent deep\ngenerative models. We use running examples to illustrate the probabilistic\nprogramming on ZhuSuan, including Bayesian logistic regression, variational\nauto-encoders, deep sigmoid belief networks and Bayesian recurrent neural\nnetworks.","url_abs":"http://arxiv.org/abs/1709.05870v1","url_pdf":"http://arxiv.org/pdf/1709.05870v1.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":"zhusuan-a-library-for-bayesian-deep-learning","repo_url":"https://github.com/thu-ml/zhusuan","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"bayesian-inference","task_name":"Bayesian Inference"},{"task_slug":"deep-learning","task_name":"Deep Learning"},{"task_slug":"probabilistic-programming","task_name":"Probabilistic Programming"},{"task_slug":"regression-1","task_name":"regression"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1709.05870","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}