{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,13]],"date-time":"2026-06-13T16:01:57Z","timestamp":1781366517669,"version":"3.54.1"},"reference-count":61,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"2","license":[{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Neural Netw. Learning Syst."],"published-print":{"date-parts":[[2026,2]]},"DOI":"10.1109\/tnnls.2025.3610024","type":"journal-article","created":{"date-parts":[[2025,10,31]],"date-time":"2025-10-31T17:12:41Z","timestamp":1761930761000},"page":"646-660","source":"Crossref","is-referenced-by-count":3,"title":["Multiscale Contrastive Learning for Node Clustering Based on Variational Graph Auto-Encoder"],"prefix":"10.1109","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1842-9756","authenticated-orcid":false,"given":"Nazila Pourhaji","family":"Aghayengejeh","sequence":"first","affiliation":[{"name":"Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, East Azarbaijan, Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5898-0871","authenticated-orcid":false,"given":"M. A.","family":"Balafar","sequence":"additional","affiliation":[{"name":"Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, East Azarbaijan, Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0779-6027","authenticated-orcid":false,"given":"Jafar","family":"Tanha","sequence":"additional","affiliation":[{"name":"Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, East Azarbaijan, Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Narjes Nikzad","family":"Khasmakhi","sequence":"additional","affiliation":[{"name":"Gisma university of Applied Sciences, Potsdam, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shervin","family":"Minaee","sequence":"additional","affiliation":[{"name":"Amazon Inc., Seattle, WA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1609.02907"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.74.035102"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-7-207"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2024.106207"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3311091"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2023.110209"},{"key":"ref7","first-page":"1","article-title":"Elbo surgery: Yet another way to carve up the variational evidence lower bound","volume-title":"Proc. Workshop Adv. Approx. Bayesian Inference","author":"Hoffman"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2020.2997772"},{"key":"ref9","first-page":"1","article-title":"Semi-implicit graph variational auto-encoders","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Hasanzadeh"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/3555809"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3380012"},{"key":"ref12","first-page":"5274","article-title":"Dirichlet graph variational autoencoder","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Li"},{"key":"ref13","article-title":"Hyperspherical variational auto-encoders","author":"Davidson","year":"2018","journal-title":"arXiv:1804.00891"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2021.3079800"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5843"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.3390\/s23104723"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00662"},{"key":"ref18","first-page":"2148","article-title":"Multi-view contrastive graph clustering","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Pan"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/601"},{"key":"ref20","article-title":"Variational graph auto-encoders","author":"Kipf","year":"2016","journal-title":"arXiv:1611.07308"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1145\/3132847.3132967"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TCE.2023.3279836"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/WACV56688.2023.00559"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2023.110935"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380214"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i7.20700"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403140"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2022.3220948"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/509"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2023.3314451"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2021.3090866"},{"key":"ref32","first-page":"1","article-title":"A simple framework for contrastive learning of visual representations","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Chen"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449802"},{"key":"ref34","first-page":"5812","article-title":"Graph contrastive learning with augmentations","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"You"},{"key":"ref35","article-title":"Deep graph contrastive representation learning","author":"Zhu","year":"2020","journal-title":"arXiv:2006.04131"},{"key":"ref36","article-title":"Representation learning with contrastive predictive coding","author":"van den Oord","year":"2018","journal-title":"arXiv:1807.03748"},{"key":"ref37","article-title":"Large-scale representation learning on graphs via bootstrapping","author":"Thakoor","year":"2021","journal-title":"arXiv:2102.06514"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-97-5572-1_18"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2024.3435887"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2022.11.019"},{"key":"ref41","first-page":"1","article-title":"Contrastive multi-view representation learning on graphs","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Hassani"},{"key":"ref42","article-title":"Deep graph infomax","author":"Veli\u010dkovi\u0107","year":"2018","journal-title":"arXiv:1809.10341"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2023.127101"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2023.12.037"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN60899.2024.10650148"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2024.121225"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2024.128629"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i6.25898"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1016\/j.ymeth.2020.08.004"},{"key":"ref50","first-page":"2434","article-title":"Graphite: Iterative generative modeling of graphs","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Grover"},{"key":"ref51","first-page":"21019","article-title":"Deconvolutional networks on graph data","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Li"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.107564"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1609\/aimag.v29i3.2157"},{"key":"ref54","first-page":"2111","article-title":"Network representation learning with rich text information","volume-title":"Proc. IJCAI","author":"Yang"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v30i1.9977"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2023.3333557"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/362"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380112"},{"key":"ref59","first-page":"5682","article-title":"Contrastive Laplacian eigenmaps","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Zhu"},{"key":"ref60","first-page":"1","article-title":"Deep graph infomax","volume-title":"Proc. Int. Conf. Learn. Represent. (ICLR)","author":"Veli\u010dkovi\u0107"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-75762-5_43"}],"container-title":["IEEE Transactions on Neural Networks and Learning Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/5962385\/11372199\/11223040.pdf?arnumber=11223040","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,9]],"date-time":"2026-02-09T21:07:08Z","timestamp":1770671228000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11223040\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2]]},"references-count":61,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.1109\/tnnls.2025.3610024","relation":{},"ISSN":["2162-237X","2162-2388"],"issn-type":[{"value":"2162-237X","type":"print"},{"value":"2162-2388","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,2]]}}}