{"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/sylvester-normalizing-flows-for-variational","title":"Sylvester Normalizing Flows for Variational Inference","arxiv_id":"1803.05649","date":"2018-03-15","proceeding":null,"authors":["Rianne van den Berg","Leonard Hasenclever","Jakub M. Tomczak","Max Welling"],"abstract":"Variational inference relies on flexible approximate posterior distributions.\nNormalizing flows provide a general recipe to construct flexible variational\nposteriors. We introduce Sylvester normalizing flows, which can be seen as a\ngeneralization of planar flows. Sylvester normalizing flows remove the\nwell-known single-unit bottleneck from planar flows, making a single\ntransformation much more flexible. We compare the performance of Sylvester\nnormalizing flows against planar flows and inverse autoregressive flows and\ndemonstrate that they compare favorably on several datasets.","url_abs":"http://arxiv.org/abs/1803.05649v2","url_pdf":"http://arxiv.org/pdf/1803.05649v2.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":"sylvester-normalizing-flows-for-variational","repo_url":"https://github.com/riannevdberg/sylvester-flows","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"sylvester-normalizing-flows-for-variational","repo_url":"https://github.com/CW-Huang/CP-Flow","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"variational-inference","task_name":"Variational Inference"}],"methods":[{"method_slug":"normalizing-flows","method_name":"Normalizing Flows"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=1803.05649","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1803.05649"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. 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