{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,30]],"date-time":"2025-08-30T17:19:36Z","timestamp":1756574376120,"version":"3.37.3"},"reference-count":40,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"4","license":[{"start":{"date-parts":[[2023,7,1]],"date-time":"2023-07-01T00:00:00Z","timestamp":1688169600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,7,1]],"date-time":"2023-07-01T00:00:00Z","timestamp":1688169600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,7,1]],"date-time":"2023-07-01T00:00:00Z","timestamp":1688169600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"JSPS KAKENHI","award":["JP20H04172"],"award-info":[{"award-number":["JP20H04172"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Netw. Sci. Eng."],"published-print":{"date-parts":[[2023,7,1]]},"DOI":"10.1109\/tnse.2023.3244590","type":"journal-article","created":{"date-parts":[[2023,2,16]],"date-time":"2023-02-16T21:21:10Z","timestamp":1676582470000},"page":"2226-2238","source":"Crossref","is-referenced-by-count":6,"title":["GraphTune: A Learning-Based Graph Generative Model With Tunable Structural Features"],"prefix":"10.1109","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9246-9740","authenticated-orcid":false,"given":"Kohei","family":"Watabe","sequence":"first","affiliation":[{"name":"Graduate School of Engineering, Nagaoka University of Technology, Nagaoka, Niigata, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shohei","family":"Nakazawa","sequence":"additional","affiliation":[{"name":"Graduate School of Engineering, Nagaoka University of Technology, Nagaoka, Niigata, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yoshiki","family":"Sato","sequence":"additional","affiliation":[{"name":"Graduate School of Engineering, Nagaoka University of Technology, Nagaoka, Niigata, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7837-2857","authenticated-orcid":false,"given":"Sho","family":"Tsugawa","sequence":"additional","affiliation":[{"name":"Faculty of Engineering, Information and Systems, University of Tsukuba, Tsukuba, Ibaraki, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9171-9448","authenticated-orcid":false,"given":"Kenji","family":"Nakagawa","sequence":"additional","affiliation":[{"name":"Graduate School of Engineering, Nagaoka University of Technology, Nagaoka, Niigata, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01418-6_41"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1088\/1742-5468\/2008\/10\/P10008"},{"key":"ref12","article-title":"Learning deep generative models of graphs","author":"li","year":"0","journal-title":"Proc 6th Int Conf Learn Representations Workshop"},{"key":"ref34","article-title":"Powerlaw: A Python package for analysis of heavy-tailed distributions","volume":"9","author":"jeff","year":"2014","journal-title":"PLoS ONE"},{"key":"ref15","first-page":"1338","article-title":"Conditional structure generation through graph variational generative adversarial nets","author":"yang","year":"0","journal-title":"Proc 33rd Conf Neural Inf Process Syst"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1080\/00018730601170527"},{"article-title":"DEFactor: Differentiable edge factorization-based probabilistic graph generation","year":"2018","author":"assouel","key":"ref14"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1016\/j.physrep.2005.10.009"},{"key":"ref31","article-title":"beta-VAE: Learning basic visual concepts with a constrained variational framework","author":"higgins","year":"0","journal-title":"Proc 5th Int Conf Learn Representations"},{"key":"ref30","first-page":"721","article-title":"gSpan: Graph-based substructure pattern mining","author":"yan","year":"0","journal-title":"Proc IEEE Int Conf Data Mining"},{"key":"ref11","first-page":"5708","article-title":"GraphRNN: Generating realistic graphs with deep auto-regressive models","author":"you","year":"0","journal-title":"Proc 35th Int Conf Mach Learn"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.69.026113"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/0378-8733(83)90021-7"},{"key":"ref32","doi-asserted-by":"crossref","DOI":"10.1038\/srep02980","article-title":"The anatomy of a scientific rumor","volume":"3","author":"domenico","year":"2013","journal-title":"Sci Rep"},{"key":"ref2","article-title":"MolGAN: An implicit generative model for small molecular graphs","author":"cao","year":"0","journal-title":"Proc 35th Int Conf Mach Learn"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDCS51616.2021.00119"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380201"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1145\/1592665.1592675"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1039\/C9SC04503A"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1145\/1772690.1772751"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3214832"},{"key":"ref18","first-page":"4839","article-title":"Hierarchical generation of molecular graphs using structural motifs","author":"jin","year":"0","journal-title":"Proc 37th Int Conf Mach Learn"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611972740.43"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.67.056104"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TFUZZ.2015.2459756"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1137\/130914218"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3098417"},{"key":"ref22","article-title":"Auto-encoding variational bayes","author":"kingma","year":"0","journal-title":"Proc 2nd Int Conf Learn Representations"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P18-1071"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11968"},{"key":"ref29","article-title":"Spectral graph theory","author":"spielman","year":"2011","journal-title":"Combinatorial Scientific Computing"},{"key":"ref8","doi-asserted-by":"crossref","first-page":"440","DOI":"10.1038\/30918","article-title":"Collective dynamics of &#x2018;small-world&#x2019; networks","volume":"393","author":"watts","year":"1998","journal-title":"Nature"},{"key":"ref7","doi-asserted-by":"crossref","first-page":"290","DOI":"10.5486\/PMD.1959.6.3-4.12","article-title":"On random graphs I","volume":"6","author":"erd\u00f6s","year":"1959","journal-title":"Publicationes Mathematicae"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1103\/RevModPhys.74.47"},{"key":"ref4","first-page":"4990","article-title":"Deep imitation learning for molecular inverse problems","author":"jonas","year":"0","journal-title":"Proc 33rd Int Conf Neural Inf Process Syst"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1186\/s13321-018-0287-6"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/3379445"},{"key":"ref5","first-page":"609","article-title":"NetGAN: Generating graphs via random walks","author":"bojchevski","year":"0","journal-title":"Proc 35th Int Conf Mach Learn"},{"key":"ref40","article-title":"Disentangling interpretable generative parameters of random and real-world graphs","author":"stoehr","year":"0","journal-title":"Proc 33rd Conf Neural Inf Process Syst Workshop"}],"container-title":["IEEE Transactions on Network Science and Engineering"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6488902\/10159461\/10043724.pdf?arnumber=10043724","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,7,10]],"date-time":"2023-07-10T19:34:21Z","timestamp":1689017661000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10043724\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,1]]},"references-count":40,"journal-issue":{"issue":"4"},"URL":"https:\/\/doi.org\/10.1109\/tnse.2023.3244590","relation":{},"ISSN":["2327-4697","2334-329X"],"issn-type":[{"type":"electronic","value":"2327-4697"},{"type":"electronic","value":"2334-329X"}],"subject":[],"published":{"date-parts":[[2023,7,1]]}}}