{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T20:10:17Z","timestamp":1780344617246,"version":"3.54.1"},"reference-count":56,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"2","license":[{"start":{"date-parts":[[2025,2,1]],"date-time":"2025-02-01T00:00:00Z","timestamp":1738368000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,2,1]],"date-time":"2025-02-01T00:00:00Z","timestamp":1738368000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,2,1]],"date-time":"2025-02-01T00:00:00Z","timestamp":1738368000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62325604"],"award-info":[{"award-number":["62325604"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62276271"],"award-info":[{"award-number":["62276271"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62006237"],"award-info":[{"award-number":["62006237"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62162024"],"award-info":[{"award-number":["62162024"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62162022"],"award-info":[{"award-number":["62162022"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004735","name":"Hunan Provincial Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2021JJ30779"],"award-info":[{"award-number":["2021JJ30779"]}],"id":[{"id":"10.13039\/501100004735","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Science and Technology Innovation Program of Hunan Province","award":["2022RC3061"],"award-info":[{"award-number":["2022RC3061"]}]},{"name":"Postgraduate Scientific Research Innovation Project in Hunan Province","award":["CX20220076"],"award-info":[{"award-number":["CX20220076"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Neural Netw. Learning Syst."],"published-print":{"date-parts":[[2025,2]]},"DOI":"10.1109\/tnnls.2024.3349850","type":"journal-article","created":{"date-parts":[[2024,1,12]],"date-time":"2024-01-12T13:58:18Z","timestamp":1705067898000},"page":"3244-3257","source":"Crossref","is-referenced-by-count":17,"title":["Revisiting Initializing Then Refining: An Incomplete and Missing Graph Imputation Network"],"prefix":"10.1109","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1353-2968","authenticated-orcid":false,"given":"Wenxuan","family":"Tu","sequence":"first","affiliation":[{"name":"School of Computer, National University of Defense Technology, Changsha, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8469-5302","authenticated-orcid":false,"given":"Bin","family":"Xiao","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9066-1475","authenticated-orcid":false,"given":"Xinwang","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Computer, National University of Defense Technology, Changsha, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1491-4594","authenticated-orcid":false,"given":"Sihang","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Intelligence Science and Technology, National University of Defense Technology, Changsha, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5726-833X","authenticated-orcid":false,"given":"Zhiping","family":"Cai","sequence":"additional","affiliation":[{"name":"School of Computer, National University of Defense Technology, Changsha, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0160-0126","authenticated-orcid":false,"given":"Jieren","family":"Cheng","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Hainan University, Haikou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.3044146"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3084195"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.3036825"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3145092"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2021.3058098"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2023.3282989"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3539618.3591711"},{"key":"ref8","article-title":"Graph convolutional matrix completion","author":"van den Berg","year":"2017","journal-title":"arXiv:1706.02263"},{"key":"ref9","first-page":"1","article-title":"Inductive matrix completion based on graph neural networks","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Zhang"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2020.06.005"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2020.11.016"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482266"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/3487553.3524238"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.3032189"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2022\/485"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623732"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939754"},{"key":"ref18","first-page":"16962","article-title":"Self-supervised heterogeneous graph pre-training based on structural clustering","volume-title":"Proc. Conf. Neural Inf. Process. Syst.","volume":"35","author":"Yang"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2021.3101356"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2022.3148299"},{"key":"ref21","article-title":"Variational graph auto-encoders","author":"Kipf","year":"2016","journal-title":"arXiv:1611.07308"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380214"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i11.17198"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i7.20726"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2023.3335222"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/494"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2019.2932096"},{"key":"ref28","first-page":"1","article-title":"Deep graph infomax","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Velickovic"},{"key":"ref29","first-page":"4116","article-title":"Contrastive multi-view representation learning on graphs","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Hassani"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380112"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449802"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2022\/418"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i14.29464"},{"key":"ref34","first-page":"1","article-title":"Generative adversarial nets","volume-title":"Proc. Conf. Neural Inf. Process. Syst.","author":"Ian"},{"key":"ref35","article-title":"Pattern recognition and machine learning","author":"Bishop","year":"2006","journal-title":"Stat. Sci."},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2019.00140"},{"key":"ref37","article-title":"Handling missing data with graph representation learning","volume-title":"Proc. Conf. Neural Inf. Process. Syst.","author":"You"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i4.25553"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449914"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3149997"},{"key":"ref41","first-page":"1","article-title":"On the unreasonable effectiveness of feature propagation in learning on graphs with missing node features","volume-title":"Proc. Learn. Graphs Conf.","author":"Rossi"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1145\/3511808.3557661"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539337"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2022.3166539"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1145\/1390156.1390294"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/467"},{"issue":"35","key":"ref47","first-page":"12758","article-title":"Navigating networks by using homophily and degree","volume-title":"Proc. Nat. Acad. Sci. USA Amer.","volume":"105","author":"Simsek"},{"key":"ref48","first-page":"1","article-title":"Auto-encoding variational Bayes","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Kingma"},{"key":"ref49","first-page":"1","article-title":"Semi-supervised classification with graph convolutional networks","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Kipf"},{"key":"ref50","first-page":"1024","article-title":"Inductive representation learning on large graphs","volume-title":"Proc. Conf. Neural Inf. Process. Syst.","author":"Hamilton"},{"key":"ref51","first-page":"1","article-title":"Graph attention networks","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Velickovic"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330941"},{"key":"ref53","first-page":"1","article-title":"Attributed random walk as matrix factorization","volume-title":"Proc. Conf. Neural Inf. Process. Syst. Workshop","author":"Chen"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33013830"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2023.3244397"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2023.3297607"}],"container-title":["IEEE Transactions on Neural Networks and Learning Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/5962385\/10877690\/10398247.pdf?arnumber=10398247","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T18:39:30Z","timestamp":1764959970000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10398247\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,2]]},"references-count":56,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.1109\/tnnls.2024.3349850","relation":{},"ISSN":["2162-237X","2162-2388"],"issn-type":[{"value":"2162-237X","type":"print"},{"value":"2162-2388","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,2]]}}}