{"id":"https://openalex.org/W4413479547","doi":"https://doi.org/10.1007/s11063-025-11773-7","title":"A Graph Generation Model for Convolutional Neural Network Architecture based on GCN and GAN","display_name":"A Graph Generation Model for Convolutional Neural Network Architecture based on GCN and GAN","publication_year":2025,"publication_date":"2025-07-08","ids":{"openalex":"https://openalex.org/W4413479547","doi":"https://doi.org/10.1007/s11063-025-11773-7"},"language":"en","primary_location":{"id":"doi:10.1007/s11063-025-11773-7","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11063-025-11773-7","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11063-025-11773-7.pdf","source":{"id":"https://openalex.org/S140962798","display_name":"Neural Processing Letters","issn_l":"1370-4621","issn":["1370-4621","1573-773X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Processing Letters","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s11063-025-11773-7.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5033057376","display_name":"Changwei Song","orcid":"https://orcid.org/0000-0003-3824-5663"},"institutions":[{"id":"https://openalex.org/I68986083","display_name":"Northwest Normal University","ror":"https://ror.org/00gx3j908","country_code":"CN","type":"education","lineage":["https://openalex.org/I68986083"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Changwei Song","raw_affiliation_strings":["College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou, 730070, China"],"affiliations":[{"raw_affiliation_string":"College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou, 730070, China","institution_ids":["https://openalex.org/I68986083"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049710229","display_name":"Yongjie Ma","orcid":"https://orcid.org/0000-0002-5062-9224"},"institutions":[{"id":"https://openalex.org/I68986083","display_name":"Northwest Normal University","ror":"https://ror.org/00gx3j908","country_code":"CN","type":"education","lineage":["https://openalex.org/I68986083"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongjie Ma","raw_affiliation_strings":["College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou, 730070, China"],"affiliations":[{"raw_affiliation_string":"College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou, 730070, China","institution_ids":["https://openalex.org/I68986083"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5033057376"],"corresponding_institution_ids":["https://openalex.org/I68986083"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":3.6402,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.93706734,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"57","issue":"4","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":0.9833999872207642,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9724000096321106,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computational-intelligence","display_name":"Computational intelligence","score":0.6726089715957642},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6140150427818298},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5847920179367065},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5052021145820618},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.43383342027664185},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39864054322242737},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.29542067646980286}],"concepts":[{"id":"https://openalex.org/C139502532","wikidata":"https://www.wikidata.org/wiki/Q1122090","display_name":"Computational intelligence","level":2,"score":0.6726089715957642},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6140150427818298},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5847920179367065},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5052021145820618},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.43383342027664185},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39864054322242737},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.29542067646980286},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s11063-025-11773-7","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11063-025-11773-7","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11063-025-11773-7.pdf","source":{"id":"https://openalex.org/S140962798","display_name":"Neural Processing Letters","issn_l":"1370-4621","issn":["1370-4621","1573-773X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Processing Letters","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s11063-025-11773-7","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11063-025-11773-7","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11063-025-11773-7.pdf","source":{"id":"https://openalex.org/S140962798","display_name":"Neural Processing Letters","issn_l":"1370-4621","issn":["1370-4621","1573-773X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Processing Letters","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G389911245","display_name":null,"funder_award_id":"62066041","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4413479547.pdf","grobid_xml":"https://content.openalex.org/works/W4413479547.grobid-xml"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W1583837637","https://openalex.org/W2194775991","https://openalex.org/W2752782242","https://openalex.org/W2953308748","https://openalex.org/W2963125010","https://openalex.org/W2963169753","https://openalex.org/W2963446712","https://openalex.org/W2963881378","https://openalex.org/W2963946985","https://openalex.org/W2964081807","https://openalex.org/W2965658867","https://openalex.org/W3035620341","https://openalex.org/W3094801149","https://openalex.org/W3169924623","https://openalex.org/W3192682950","https://openalex.org/W3206736029","https://openalex.org/W3214264009","https://openalex.org/W4200163348","https://openalex.org/W4214868967","https://openalex.org/W4226401862","https://openalex.org/W4285306522","https://openalex.org/W4306733841","https://openalex.org/W4313166273","https://openalex.org/W4367174982","https://openalex.org/W4383750379","https://openalex.org/W4386071638","https://openalex.org/W6702248584"],"related_works":["https://openalex.org/W4391621807","https://openalex.org/W4321487865","https://openalex.org/W4313906399","https://openalex.org/W4391621790","https://openalex.org/W4239306820","https://openalex.org/W4391266461","https://openalex.org/W2590798552","https://openalex.org/W2811106690","https://openalex.org/W2947043951","https://openalex.org/W4399188509"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"Neural":[3,91],"Architecture":[4],"Search":[5],"(NAS)":[6],"has":[7],"garnered":[8],"widespread":[9],"attention":[10],"in":[11,22,71,138,147,168],"the":[12,24,49,68,126,130,156,183,186],"field":[13],"of":[14,26,80,128,153,170],"deep":[15,27,84],"learning":[16],"due":[17],"to":[18,42,87,121],"its":[19],"significant":[20,69],"potential":[21],"automating":[23],"construction":[25],"models.":[28],"However,":[29],"existing":[30],"NAS":[31],"methods":[32],"primarily":[33],"focus":[34],"on":[35,112,155],"optimizing":[36],"network":[37,46,92,123],"architecture,":[38],"utilizing":[39,83],"search":[40,50],"strategies":[41],"find":[43],"a":[44,107],"high-performing":[45],"architecture":[47,93,142],"within":[48],"space":[51],"as":[52,54,97],"effectively":[53],"possible.":[55],"And":[56],"this":[57,148],"process":[58,137],"often":[59],"requires":[60],"repetitive":[61,131,189],"and":[62,65,117,132,135,178,191],"continuous":[63,133],"searching":[64,134,190],"evaluation.":[66,192],"With":[67,125],"advancements":[70],"Artificial":[72],"Intelligence":[73],"Generated":[74],"Content":[75],"(AIGC),":[76],"an":[77,151],"increasing":[78],"number":[79],"researchers":[81],"are":[82],"generative":[85],"models":[86,167],"create":[88],"graph":[89,108],"data.":[90],"can":[94],"be":[95],"viewed":[96],"Directed":[98],"Acyclic":[99],"Graphs(DAG)":[100],"with":[101],"labeled":[102],"nodes.":[103],"Therefore,":[104],"we":[105],"propose":[106],"generation":[109],"model":[110],"based":[111],"Graph":[113],"Convolutional":[114],"Network":[115],"(GCN)":[116],"Generative":[118],"Adversarial":[119],"Network(GAN)":[120],"generate":[122],"architecture.":[124],"aim":[127],"avoiding":[129,185],"evaluation":[136],"NAS.":[139],"The":[140],"CNN":[141,166],"generated":[143,180],"by":[144,182],"our":[145],"algorithm":[146],"paper":[149],"achieves":[150],"accuracy":[152],"94.37%":[154],"CIFAR-10":[157],"dataset.":[158],"While":[159],"it":[160,172],"may":[161],"not":[162],"outperform":[163],"many":[164],"other":[165],"terms":[169],"performance,":[171],"doesn\u2019t":[173],"require":[174],"any":[175],"expert":[176],"knowledge":[177],"is":[179],"automatically":[181],"model,":[184],"need":[187],"for":[188]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
