{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,27]],"date-time":"2025-04-27T05:00:20Z","timestamp":1745730020558,"version":"3.37.3"},"reference-count":68,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"6","license":[{"start":{"date-parts":[[2023,11,1]],"date-time":"2023-11-01T00:00:00Z","timestamp":1698796800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,11,1]],"date-time":"2023-11-01T00:00:00Z","timestamp":1698796800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,11,1]],"date-time":"2023-11-01T00:00:00Z","timestamp":1698796800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100006602","name":"Air Force Research Laboratory","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006602","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000185","name":"Defense Advanced Research Projects Agency","doi-asserted-by":"publisher","award":["FA8750-20-2-1001"],"award-info":[{"award-number":["FA8750-20-2-1001"]}],"id":[{"id":"10.13039\/100000185","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Netw. Sci. Eng."],"published-print":{"date-parts":[[2023,11]]},"DOI":"10.1109\/tnse.2023.3260730","type":"journal-article","created":{"date-parts":[[2023,4,3]],"date-time":"2023-04-03T17:36:13Z","timestamp":1680543373000},"page":"3384-3395","source":"Crossref","is-referenced-by-count":2,"title":["Clustered Graph Matching for Label Recovery and Graph Classification"],"prefix":"10.1109","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4064-1414","authenticated-orcid":false,"given":"Zhirui","family":"Li","sequence":"first","affiliation":[{"name":"Department of Mathematics, University of Maryland, College Park, MD, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3071-9043","authenticated-orcid":false,"given":"Jes\u00fas","family":"Arroyo","sequence":"additional","affiliation":[{"name":"Department of Statistics, Texas A&M University, College Station, TX, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2989-010X","authenticated-orcid":false,"given":"Konstantinos","family":"Pantazis","sequence":"additional","affiliation":[{"name":"Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5594-8956","authenticated-orcid":false,"given":"Vince","family":"Lyzinski","sequence":"additional","affiliation":[{"name":"Department of Mathematics, University of Maryland, College Park, MD, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1038\/nrn2575"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1214\/17-AOS1623"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/S1389-1286(00)00083-9"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.3150\/21-BEJ1376"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1142\/S0218001404003228"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.105.054311"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-statistics-042720-023234"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2018.2885968"},{"key":"ref53","first-page":"2539","article-title":"Weisfeiler-Lehman graph kernels","volume":"12","author":"shervashidze","year":"2011","journal-title":"J Mach Learn Res"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1911030117"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/bti1007"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1080\/10618600.2016.1193505"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1214\/11-AOS904"},{"key":"ref54","first-page":"2887","article-title":"Matched filters for noisy induced subgraph detection","volume":"42","author":"sussman","year":"2020","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"article-title":"Exact alignment recovery for correlated Erdos Renyi graphs","year":"2017","author":"cullina","key":"ref17"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/2964791.2901460"},{"article-title":"Bias-variance tradeoffs in joint spectral embeddings","year":"2020","author":"draves","key":"ref19"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2006.01.021"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2020.04.004"},{"key":"ref50","first-page":"22259","article-title":"Correlated stochastic block models: Exact graph matching with applications to recovering communities","volume":"34","author":"racz","year":"0","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v31i1.10839"},{"key":"ref45","first-page":"20","article-title":"Learning convolutional neural networks for graphs","author":"niepert","year":"0","journal-title":"Proc 33rd Int Conf Mach Learn"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1145\/2020408.2020596"},{"key":"ref47","first-page":"709","article-title":"Optimal de-anonymization in random graphs with community structure","author":"onaran","year":"0","journal-title":"Proc IEEE 50th Asilomar Conf Signals Syst Comput"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1137\/S003614450342480"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.66.016128"},{"article-title":"The multiple random dot product graph model","year":"2018","author":"nielsen","key":"ref44"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1093\/oso\/9780198805090.001.0001"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1080\/10618600.2014.951049"},{"key":"ref8","first-page":"9190","article-title":"(Nearly) efficient algorithms for the graph matching problem on correlated random graphs","volume":"32","author":"barak","year":"0","journal-title":"Proc Adv Neural Inf Process Syst"},{"journal-title":"Network Science","year":"2016","author":"barab\u00e1si","key":"ref7"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0907096106"},{"key":"ref4","article-title":"Network classification with applications to brain connectomics","volume":"13","author":"reli\u00f3n","year":"2019","journal-title":"Ann Appl Statist"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1080\/10618600.2021.1872582"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/s13171-015-0071-x"},{"key":"ref5","first-page":"1","article-title":"Statistical inference on random dot product graphs: A survey","volume":"18","author":"athreya","year":"2018","journal-title":"J Mach Learn Res"},{"key":"ref40","first-page":"34","article-title":"Modeling of social network using graph theoretical approach","author":"mishra","year":"0","journal-title":"Proc Int J Comput Appl Int Conf Microelectronics Circuits Syst"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICDMW.2017.132"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1137\/07070111X"},{"article-title":"Seeded graph matching via joint optimization of fidelity and commensurability","year":"2014","author":"lyzinski","key":"ref37"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2018.2808999"},{"key":"ref31","article-title":"A high-throughput pipeline identifies robust connectomes but troublesome variability","author":"kiar","year":"2018","journal-title":"BioRxiv"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/0378-8733(83)90021-7"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1214\/19-AOS1820"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4939-0983-4"},{"key":"ref2","first-page":"1","article-title":"Inference for multiple heterogeneous networks with a common invariant subspace","volume":"22","author":"arroyo","year":"2021","journal-title":"J Mach Learn Res"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.19195\/0208-4147.37.2.2"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1093\/imaiai\/iaz031"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2424894"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2018.09.014"},{"key":"ref68","first-page":"1","article-title":"An open science resource for establishing reliability and reproducibility in functional connectomics","volume":"1","author":"zuo","year":"2014","journal-title":"Data Science Journal"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/s41109-021-00398-z"},{"key":"ref67","first-page":"1","article-title":"Network regression with graph Laplacians","volume":"23","author":"zhou","year":"2022","journal-title":"J Mach Learn Res"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1214\/16-AOAS1015"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1142\/S0218001414500013"},{"key":"ref20","first-page":"2224","article-title":"Convolutional networks on graphs for learning molecular fingerprints","volume":"28","author":"duvenaud","year":"0","journal-title":"Proc Adv in Neural Inf Process Syst"},{"article-title":"Nonparametric graphon estimation","year":"2013","author":"wolfe","key":"ref64"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2019.2948619"},{"key":"ref22","first-page":"2985","article-title":"Spectral graph matching and regularized quadratic relaxations: Algorithm and theory","author":"fan","year":"0","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1145\/2911996.2912035"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/BF01895716"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2022.3169005"},{"key":"ref28","first-page":"313","article-title":"Migraine: MRI graph reliability analysis and inference for connectomics","author":"gray","year":"0","journal-title":"Proc Glob Conf Signal Inf Process"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1561\/2200000005"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1198\/016214502388618906"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1007\/s00357-015-9170-6"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2020.117493"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2012.235"}],"container-title":["IEEE Transactions on Network Science and Engineering"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6488902\/10294312\/10091478.pdf?arnumber=10091478","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,29]],"date-time":"2023-11-29T15:39:09Z","timestamp":1701272349000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10091478\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11]]},"references-count":68,"journal-issue":{"issue":"6"},"URL":"https:\/\/doi.org\/10.1109\/tnse.2023.3260730","relation":{},"ISSN":["2327-4697","2334-329X"],"issn-type":[{"type":"electronic","value":"2327-4697"},{"type":"electronic","value":"2334-329X"}],"subject":[],"published":{"date-parts":[[2023,11]]}}}