{"id":"https://openalex.org/W4206589259","doi":"https://doi.org/10.1109/ic-nidc54101.2021.9660574","title":"Degree Matters: Assessing the Generalization of Graph Neural Network","display_name":"Degree Matters: Assessing the Generalization of Graph Neural Network","publication_year":2021,"publication_date":"2021-11-17","ids":{"openalex":"https://openalex.org/W4206589259","doi":"https://doi.org/10.1109/ic-nidc54101.2021.9660574"},"language":"en","primary_location":{"id":"doi:10.1109/ic-nidc54101.2021.9660574","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ic-nidc54101.2021.9660574","pdf_url":null,"source":{"id":"https://openalex.org/S4363608589","display_name":"2021 7th IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 7th IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5005155456","display_name":"Hyunmok Park","orcid":null},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Hyunmok Park","raw_affiliation_strings":["Hanyang University,Department of Electronic Engineering,Seoul,Korea"],"affiliations":[{"raw_affiliation_string":"Hanyang University,Department of Electronic Engineering,Seoul,Korea","institution_ids":["https://openalex.org/I4575257"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063688088","display_name":"Kijung Yoon","orcid":"https://orcid.org/0000-0001-5574-3299"},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kijung Yoon","raw_affiliation_strings":["Hanyang University,Department of Electronic Engineering,Seoul,Korea"],"affiliations":[{"raw_affiliation_string":"Hanyang University,Department of Electronic Engineering,Seoul,Korea","institution_ids":["https://openalex.org/I4575257"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5005155456"],"corresponding_institution_ids":["https://openalex.org/I4575257"],"apc_list":null,"apc_paid":null,"fwci":0.1257,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.40194429,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9991999864578247,"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"}},"topics":[{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9991999864578247,"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"}},{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9930999875068665,"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"}},{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.9804999828338623,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7025744915008545},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6928940415382385},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.6538123488426208},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6222887635231018},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5630349516868591},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5510490536689758},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4788236916065216},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4695014953613281},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.45833805203437805},{"id":"https://openalex.org/keywords/degree","display_name":"Degree (music)","score":0.44446682929992676},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20926350355148315}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7025744915008545},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6928940415382385},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.6538123488426208},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6222887635231018},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5630349516868591},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5510490536689758},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4788236916065216},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4695014953613281},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.45833805203437805},{"id":"https://openalex.org/C2775997480","wikidata":"https://www.wikidata.org/wiki/Q586277","display_name":"Degree (music)","level":2,"score":0.44446682929992676},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20926350355148315},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ic-nidc54101.2021.9660574","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ic-nidc54101.2021.9660574","pdf_url":null,"source":{"id":"https://openalex.org/S4363608589","display_name":"2021 7th IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 7th IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G186887544","display_name":null,"funder_award_id":"NRF-2018R1C1B5086404","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320321681","display_name":"Ministry of Trade, Industry and Energy","ror":"https://ror.org/008nkqk13"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W2059448777","https://openalex.org/W2090361527","https://openalex.org/W2112090702","https://openalex.org/W2137576513","https://openalex.org/W2299115575","https://openalex.org/W2606780347","https://openalex.org/W2607264901","https://openalex.org/W2626454479","https://openalex.org/W2805516822","https://openalex.org/W2889399096","https://openalex.org/W2946985165","https://openalex.org/W2947795716","https://openalex.org/W2950898568","https://openalex.org/W2962711740","https://openalex.org/W2964084343","https://openalex.org/W2964113829","https://openalex.org/W2970375342","https://openalex.org/W3009052662","https://openalex.org/W3009381467","https://openalex.org/W3034214690","https://openalex.org/W3038228403","https://openalex.org/W3040986370","https://openalex.org/W3088584794","https://openalex.org/W3093053358","https://openalex.org/W3100078588","https://openalex.org/W4288108826","https://openalex.org/W4293651439","https://openalex.org/W4297733535","https://openalex.org/W4323347028","https://openalex.org/W6680409316","https://openalex.org/W6685350579","https://openalex.org/W6690815549","https://openalex.org/W6697873463","https://openalex.org/W6736685754","https://openalex.org/W6739530971","https://openalex.org/W6744557953","https://openalex.org/W6745537798","https://openalex.org/W6751672534","https://openalex.org/W6751796012","https://openalex.org/W6754929296","https://openalex.org/W6763152702","https://openalex.org/W6763392795","https://openalex.org/W6763393335","https://openalex.org/W6767660056","https://openalex.org/W6773956970","https://openalex.org/W6774263817","https://openalex.org/W6776488958","https://openalex.org/W6779715462","https://openalex.org/W6779874303","https://openalex.org/W6780395004","https://openalex.org/W6783235295","https://openalex.org/W6783916811"],"related_works":["https://openalex.org/W2989932438","https://openalex.org/W1629725936","https://openalex.org/W2535616844","https://openalex.org/W4300606464","https://openalex.org/W2950385349","https://openalex.org/W51807384","https://openalex.org/W2763489384","https://openalex.org/W2516632589","https://openalex.org/W3166852774","https://openalex.org/W2355108509"],"abstract_inverted_index":{"Graph":[0],"neural":[1,11,29,42,57,192],"network":[2],"(GNN)":[3],"is":[4,22,129,148,188],"a":[5,20,26,77,150],"general":[6,82],"framework":[7],"for":[8,80],"using":[9,41],"deep":[10],"networks":[12],"on":[13,67,178],"graph":[14,109,146],"data.":[15],"The":[16,44],"defining":[17],"feature":[18],"of":[19,28,93,118,131,154,180,184],"GNN":[21],"that":[23,48,122],"it":[24],"uses":[25],"form":[27],"message":[30,45],"passing":[31,46],"where":[32,96],"vector":[33],"messages":[34],"are":[35,204],"exchanged":[36],"between":[37],"nodes":[38],"and":[39,98,111,168],"updated":[40],"networks.":[43],"operation":[47],"underlies":[49],"GNNs":[50,72,138,158,177,195],"has":[51,64],"recently":[52],"been":[53,65],"applied":[54],"to":[55,141],"develop":[56],"approximate":[58],"inference":[59,83,193,210],"algorithms,":[60],"but":[61],"little":[62],"work":[63],"done":[66],"understanding":[68],"under":[69],"what":[70],"conditions":[71],"can":[73,139],"be":[74],"used":[75],"as":[76],"core":[78],"module":[79],"building":[81],"models.":[84],"To":[85],"study":[86],"this":[87],"question,":[88],"we":[89],"consider":[90],"the":[91,108,115,124,132,145,155,160,173,201,209],"task":[92],"out-of-distribution":[94],"generalization":[95,156],"training":[97,167,176],"test":[99,169],"data":[100],"have":[101],"different":[102],"distributions,":[103],"by":[104,194],"systematically":[105],"investigating":[106],"how":[107],"size":[110,147,186],"structural":[112],"properties":[113],"affect":[114],"inferential":[116],"performance":[117],"GNNs.":[119],"We":[120],"find":[121],"(1)":[123],"average":[125,161],"unique":[126],"node":[127,162],"degree":[128,163,182],"one":[130],"key":[133],"features":[134],"in":[135,157],"predicting":[136],"whether":[137],"generalize":[140],"unseen":[142],"graphs;":[143],"(2)":[144],"not":[149,189],"fundamental":[151],"limiting":[152],"factor":[153],"when":[159,200],"remains":[164],"invariant":[165],"across":[166],"distributions;":[170],"(3)":[171],"despite":[172],"size-invariant":[174],"generalization,":[175],"graphs":[179],"high":[181],"(and":[183],"large":[185],"consequently)":[187],"trivial":[190],"(4)":[191],"outperforms":[196],"algorithmic":[197],"inferences":[198],"especially":[199],"pairwise":[202],"potentials":[203],"strong,":[205],"which":[206],"naturally":[207],"makes":[208],"problem":[211],"harder.":[212]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}