{"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/a-generalization-of-convolutional-neural","title":"A Generalization of Convolutional Neural Networks to Graph-Structured Data","arxiv_id":"1704.08165","date":"2017-04-26","proceeding":null,"authors":["Yotam Hechtlinger","Purvasha Chakravarti","Jining Qin"],"abstract":"This paper introduces a generalization of Convolutional Neural Networks\n(CNNs) from low-dimensional grid data, such as images, to graph-structured\ndata. We propose a novel spatial convolution utilizing a random walk to uncover\nthe relations within the input, analogous to the way the standard convolution\nuses the spatial neighborhood of a pixel on the grid. The convolution has an\nintuitive interpretation, is efficient and scalable and can also be used on\ndata with varying graph structure. Furthermore, this generalization can be\napplied to many standard regression or classification problems, by learning the\nthe underlying graph. We empirically demonstrate the performance of the\nproposed CNN on MNIST, and challenge the state-of-the-art on Merck molecular\nactivity data set.","url_abs":"http://arxiv.org/abs/1704.08165v1","url_pdf":"http://arxiv.org/pdf/1704.08165v1.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":"a-generalization-of-convolutional-neural","repo_url":"https://github.com/hechtlinger/graph_cnn","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"regression-1","task_name":"regression"}],"methods":[{"method_slug":"convolution","method_name":"Convolution"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1704.08165","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}