{"title":"神经网络处理图信号的研究进展","authors":"Yuzhong Yan, C. Akujuobi","doi":"10.46300/9106.2022.16.91","DOIUrl":null,"url":null,"abstract":"In this paper, we review the development of the traditional graph signal processing methodology, and the recent research areas that are applying graph neural networks on graph data. For the popular topics on processing the graph data with neural networks, the main models/frameworks, dataset and applications are discussed in details. Some challenges and open problems are provided, which serve as the guidance for future research directions.","PeriodicalId":13929,"journal":{"name":"International Journal of Circuits, Systems and Signal Processing","volume":"7 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Review of Graph Signal Processing with Neural Networks\",\"authors\":\"Yuzhong Yan, C. Akujuobi\",\"doi\":\"10.46300/9106.2022.16.91\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we review the development of the traditional graph signal processing methodology, and the recent research areas that are applying graph neural networks on graph data. For the popular topics on processing the graph data with neural networks, the main models/frameworks, dataset and applications are discussed in details. Some challenges and open problems are provided, which serve as the guidance for future research directions.\",\"PeriodicalId\":13929,\"journal\":{\"name\":\"International Journal of Circuits, Systems and Signal Processing\",\"volume\":\"7 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-02-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Circuits, Systems and Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.46300/9106.2022.16.91\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Circuits, Systems and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46300/9106.2022.16.91","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Engineering","Score":null,"Total":0}
A Review of Graph Signal Processing with Neural Networks
In this paper, we review the development of the traditional graph signal processing methodology, and the recent research areas that are applying graph neural networks on graph data. For the popular topics on processing the graph data with neural networks, the main models/frameworks, dataset and applications are discussed in details. Some challenges and open problems are provided, which serve as the guidance for future research directions.
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