{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T20:20:59Z","timestamp":1740169259651,"version":"3.37.3"},"reference-count":46,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100003819","name":"Natural Science Foundation of Hubei Province","doi-asserted-by":"publisher","award":["2021CFB139"],"award-info":[{"award-number":["2021CFB139"]}],"id":[{"id":"10.13039\/501100003819","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["2662020XXQD002"],"award-info":[{"award-number":["2662020XXQD002"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shenzhen College Stability Support Plan","award":["GXWD20201230155427003-20200824113231001"],"award-info":[{"award-number":["GXWD20201230155427003-20200824113231001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2022]]},"DOI":"10.1109\/access.2022.3176634","type":"journal-article","created":{"date-parts":[[2022,5,20]],"date-time":"2022-05-20T19:33:38Z","timestamp":1653075218000},"page":"56482-56492","source":"Crossref","is-referenced-by-count":0,"title":["Schatten Graph Neural Networks"],"prefix":"10.1109","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3540-5775","authenticated-orcid":false,"given":"Youfa","family":"Liu","sequence":"first","affiliation":[{"name":"College of Informatics, Huazhong Agricultural University, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1970-1993","authenticated-orcid":false,"given":"Yongyong","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Computer Science, Harbin Institute of Technology, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2567-2722","authenticated-orcid":false,"given":"Guo","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Business, Hubei University, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiawei","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Informatics, Huazhong Agricultural University, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313488"},{"key":"ref2","first-page":"127","article-title":"Graph neural networks for the prediction of protein-protein interfaces","volume-title":"Proc. ESANN","author":"Pancino"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.3301485"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2978386"},{"key":"ref5","article-title":"Semi-supervised classification with graph convolutional networks","author":"Kipf","year":"2016","journal-title":"arXiv:1609.02907"},{"key":"ref6","first-page":"2428","article-title":"Link prediction based on graph neural networks","volume-title":"Proc. NeurIPS","author":"Zhang"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330950"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN52387.2021.9533519"},{"key":"ref9","article-title":"Generalization and representational limits of graph neural networks","author":"Garg","year":"2020","journal-title":"arXiv:2002.06157"},{"key":"ref10","article-title":"Graph attention networks","author":"Veli\u010dkovi\u0107","year":"2017","journal-title":"arXiv:1710.10903"},{"key":"ref11","article-title":"A unified view on graph neural networks as graph signal denoising","author":"Ma","year":"2020","journal-title":"arXiv:2010.01777"},{"key":"ref12","first-page":"6837","article-title":"Elastic graph neural networks","volume-title":"Proc. ICML","author":"Liu"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1088\/0266-5611\/29\/2\/025011"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2022.3201243"},{"key":"ref15","first-page":"1115","article-title":"Adversarial attack on graph structured data","volume-title":"Proc. ICML","author":"Dai"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2019.2891760"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.526"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1198\/016214501753382273"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.2307\/1269656"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2008.927346"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46454-1_41"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1137\/0326071"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/s10915-018-0757-z"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ISIT44484.2020.9174216"},{"key":"ref25","first-page":"2399","article-title":"Manifold regularization: A geometric framework for learning from labeled and unlabeled examples","volume":"7","author":"Belkin","year":"2006","journal-title":"J. Mach. Learn. Res."},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v31i1.10646"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4419-9467-7"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/S0166-8641(96)00142-3"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1609\/aimag.v29i3.2157"},{"key":"ref30","article-title":"Pitfalls of graph neural network evaluation","author":"Shchur","year":"2018","journal-title":"arXiv:1811.05868"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/1134271.1134277"},{"key":"ref32","first-page":"6861","article-title":"Simplifying graph convolutional networks","volume-title":"Proc. PMLR","author":"Wu"},{"key":"ref33","article-title":"Inductive representation learning on large graphs","author":"Hamilton","year":"2017","journal-title":"arXiv:1706.02216"},{"key":"ref34","article-title":"Predict then propagate: Graph neural networks meet personalized PageRank","author":"Gasteiger","year":"2018","journal-title":"arXiv:1810.05997"},{"key":"ref35","first-page":"1569","article-title":"Perturbing eigenvalues with residual learning in graph convolutional neural networks","volume-title":"Proc. ACML","author":"Yao"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/872"},{"key":"ref37","article-title":"DeepRobust: A PyTorch library for adversarial attacks and defenses","author":"Li","year":"2020","journal-title":"arXiv:2005.06149"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403049"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2016.2599290"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1016\/j.cam.2014.02.015"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1088\/0266-5611\/27\/12\/125007"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1007\/s10444-020-09840-9"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3167640"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3133496"},{"key":"ref45","first-page":"9323","article-title":"E(n) equivariant graph neural networks","volume-title":"Proc. ICML","author":"Satorras"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1007\/s11071-021-07160-1"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/9668973\/09779228.pdf?arnumber=9779228","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,22]],"date-time":"2024-01-22T23:07:46Z","timestamp":1705964866000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9779228\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"references-count":46,"URL":"https:\/\/doi.org\/10.1109\/access.2022.3176634","relation":{},"ISSN":["2169-3536"],"issn-type":[{"type":"electronic","value":"2169-3536"}],"subject":[],"published":{"date-parts":[[2022]]}}}