{"id":"https://openalex.org/W4385768079","doi":"https://doi.org/10.24963/ijcai.2023/449","title":"Multi-View Robust Graph Representation Learning for Graph Classification","display_name":"Multi-View Robust Graph Representation Learning for Graph Classification","publication_year":2023,"publication_date":"2023-08-01","ids":{"openalex":"https://openalex.org/W4385768079","doi":"https://doi.org/10.24963/ijcai.2023/449"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2023/449","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2023/449","pdf_url":"https://www.ijcai.org/proceedings/2023/0449.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2023/0449.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037739393","display_name":"Guanghui Ma","orcid":"https://orcid.org/0000-0002-9290-1724"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guanghui Ma","raw_affiliation_strings":["School of Computer Science and Engineering, Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086470621","display_name":"Chunming Hu","orcid":"https://orcid.org/0000-0002-9502-3955"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunming Hu","raw_affiliation_strings":["College of Software, Beihang University, Beijing, China","School of Computer Science and Engineering, Beihang University, Beijing, China","Zhongguancun Laboratory, Beijing, China","College of Software, Beihang University, Beijing, China; School of Computer Science and Engineering, Beihang University, Beijing, China; Zhongguancun Laboratory, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Software, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"Zhongguancun Laboratory, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"College of Software, Beihang University, Beijing, China; School of Computer Science and Engineering, Beihang University, Beijing, China; Zhongguancun Laboratory, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100648472","display_name":"Ling Ge","orcid":"https://orcid.org/0000-0003-1896-9162"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ling Ge","raw_affiliation_strings":["School of Computer Science and Engineering, Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100608341","display_name":"Hong Zhang","orcid":"https://orcid.org/0009-0002-6524-2572"},"institutions":[{"id":"https://openalex.org/I4210087772","display_name":"National Computer Network Emergency Response Technical Team/Coordination Center of Chinar","ror":"https://ror.org/00247dh76","country_code":"CN","type":"nonprofit","lineage":["https://openalex.org/I4210087772"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Zhang","raw_affiliation_strings":["National Computer Network Emergency Response Technical Team / Coordination Center of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Computer Network Emergency Response Technical Team / Coordination Center of China","institution_ids":["https://openalex.org/I4210087772"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4037","last_page":"4045"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998999834060669,"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":0.9998999834060669,"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/T11719","display_name":"Data Quality and Management","score":0.991100013256073,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9883999824523926,"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/computer-science","display_name":"Computer science","score":0.7689552307128906},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6086574196815491},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5737483501434326},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5680243372917175},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5619323253631592},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5363876223564148},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.4430468678474426},{"id":"https://openalex.org/keywords/external-data-representation","display_name":"External Data Representation","score":0.43383270502090454},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4225912094116211},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.37617161870002747},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3484775424003601}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7689552307128906},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6086574196815491},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5737483501434326},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5680243372917175},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5619323253631592},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5363876223564148},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.4430468678474426},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.43383270502090454},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4225912094116211},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.37617161870002747},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3484775424003601},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2023/449","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2023/449","pdf_url":"https://www.ijcai.org/proceedings/2023/0449.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2023/449","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2023/449","pdf_url":"https://www.ijcai.org/proceedings/2023/0449.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.7300000190734863,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320329053","display_name":"Beijing Advanced Innovation Center for Big Data and Brain Computing","ror":null}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4385768079.pdf"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W2964015378","https://openalex.org/W2997079913","https://openalex.org/W3033039844","https://openalex.org/W3034693603","https://openalex.org/W3035237749","https://openalex.org/W3042313988","https://openalex.org/W3086452730","https://openalex.org/W3095602948","https://openalex.org/W3111920969","https://openalex.org/W3116239416","https://openalex.org/W3135138557","https://openalex.org/W3156636935","https://openalex.org/W3170424177","https://openalex.org/W3186377753","https://openalex.org/W3188982020","https://openalex.org/W4221023051","https://openalex.org/W4221150126","https://openalex.org/W4221155002","https://openalex.org/W4224318590","https://openalex.org/W4225977739","https://openalex.org/W4283065718","https://openalex.org/W4283818432","https://openalex.org/W4286893581","https://openalex.org/W4288275971","https://openalex.org/W4290874961","https://openalex.org/W4290948450","https://openalex.org/W4306317355","https://openalex.org/W4382202731","https://openalex.org/W4385572972"],"related_works":["https://openalex.org/W3112714922","https://openalex.org/W3119773509","https://openalex.org/W3208297503","https://openalex.org/W2889153461","https://openalex.org/W2964117661","https://openalex.org/W4388405611","https://openalex.org/W2619127353","https://openalex.org/W2952512863","https://openalex.org/W3134504629","https://openalex.org/W2938696877"],"abstract_inverted_index":{"The":[0],"robustness":[1],"of":[2,26,31,165],"graph":[3,50,83,117],"classification":[4,51,84],"models":[5,52],"plays":[6],"an":[7,93],"essential":[8],"role":[9],"in":[10,29,67],"providing":[11],"highly":[12],"reliable":[13],"applications.":[14],"Previous":[15],"studies":[16],"along":[17],"this":[18],"line":[19],"primarily":[20],"focus":[21],"on":[22,109,158],"seeking":[23],"the":[24,27,114,121,136,150,163],"stability":[25],"model":[28,81],"terms":[30],"overall":[32],"data":[33,39],"metrics":[34],"(e.g.,":[35],"accuracy)":[36],"when":[37],"facing":[38],"perturbations,":[40],"such":[41],"as":[42],"removing":[43],"edges.":[44],"Empirically,":[45],"we":[46,74,91,126],"find":[47],"that":[48,86],"these":[49,72],"also":[53],"suffer":[54],"from":[55],"semantic":[56,107,122],"bias":[57,123],"and":[58,116,145,156],"confidence":[59,151],"collapse":[60,152],"issues,":[61,73],"which":[62,99,134],"substantially":[63],"hinder":[64],"their":[65],"applicability":[66],"real-world":[68],"scenarios.":[69],"To":[70],"address":[71],"present":[75],"MGRL,":[76],"a":[77,128],"multi-view":[78],"representation":[79,96,131],"learning":[80,97,103,132],"for":[82],"tasks":[85],"achieves":[87],"robust":[88],"results.":[89],"Firstly,":[90],"proposes":[92,127],"instance-view":[94],"consistency":[95],"method,":[98,133],"utilizes":[100],"multi-granularity":[101],"contrastive":[102],"technique":[104,141],"to":[105,142],"perform":[106],"constraints":[108],"instance":[110],"representations":[111],"at":[112],"both":[113],"node":[115],"levels,":[118],"thus":[119],"alleviating":[120],"issue.":[124],"Secondly,":[125],"class-view":[129],"discriminative":[130],"employs":[135],"prototype-driven":[137],"class":[138],"distance":[139],"optimization":[140],"adjust":[143],"intra-":[144],"inter-class":[146],"distances,":[147],"thereby":[148],"mitigating":[149],"issue.Finally,":[153],"extensive":[154],"experiments":[155],"visualizations":[157],"eight":[159],"benchmark":[160],"dataset":[161],"demonstrate":[162],"effectiveness":[164],"MGRL.":[166]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}