{"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/sampling-theory-for-graph-signals-on-product","title":"Sampling Theory for Graph Signals on Product Graphs","arxiv_id":"1809.10049","date":"2018-09-26","proceeding":null,"authors":["Rohan Varma","Jelena Kovačević"],"abstract":"In this paper, we extend the sampling theory on graphs by constructing a\nframework that exploits the structure in product graphs for efficient sampling\nand recovery of bandlimited graph signals that lie on them. Product graphs are\ngraphs that are composed from smaller graph atoms; we motivate how this model\nis a flexible and useful way to model richer classes of data that can be\nmulti-modal in nature. Previous works have established a sampling theory on\ngraphs for bandlimited signals. Importantly, the framework achieves significant\nsavings in both sample complexity and computational complexity","url_abs":"http://arxiv.org/abs/1809.10049v1","url_pdf":"http://arxiv.org/pdf/1809.10049v1.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":"sampling-theory-for-graph-signals-on-product","repo_url":"https://github.com/CrowdArt/node-chat-app","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"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}