{"id":"https://openalex.org/W3190214286","doi":"https://doi.org/10.24963/ijcai.2021/204","title":"Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning","display_name":"Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning","publication_year":2021,"publication_date":"2021-08-01","ids":{"openalex":"https://openalex.org/W3190214286","doi":"https://doi.org/10.24963/ijcai.2021/204","mag":"3190214286"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2021/204","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2021/204","pdf_url":"https://www.ijcai.org/proceedings/2021/0204.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2021/0204.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101484129","display_name":"Ming Jin","orcid":"https://orcid.org/0000-0001-7909-4545"},"institutions":[{"id":"https://openalex.org/I2801239119","display_name":"Australian Regenerative Medicine Institute","ror":"https://ror.org/02qa5kg76","country_code":"AU","type":"facility","lineage":["https://openalex.org/I2801037857","https://openalex.org/I2801239119","https://openalex.org/I56590836"]},{"id":"https://openalex.org/I56590836","display_name":"Monash University","ror":"https://ror.org/02bfwt286","country_code":"AU","type":"education","lineage":["https://openalex.org/I56590836"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Ming Jin","raw_affiliation_strings":["Monash University","Department of Data Science and AI, Faculty of IT, Monash University, Australia"],"affiliations":[{"raw_affiliation_string":"Monash University","institution_ids":["https://openalex.org/I2801239119","https://openalex.org/I56590836"]},{"raw_affiliation_string":"Department of Data Science and AI, Faculty of IT, Monash University, Australia","institution_ids":["https://openalex.org/I56590836"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028938739","display_name":"Yizhen Zheng","orcid":"https://orcid.org/0000-0002-3540-8845"},"institutions":[{"id":"https://openalex.org/I2801239119","display_name":"Australian Regenerative Medicine Institute","ror":"https://ror.org/02qa5kg76","country_code":"AU","type":"facility","lineage":["https://openalex.org/I2801037857","https://openalex.org/I2801239119","https://openalex.org/I56590836"]},{"id":"https://openalex.org/I56590836","display_name":"Monash University","ror":"https://ror.org/02bfwt286","country_code":"AU","type":"education","lineage":["https://openalex.org/I56590836"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yizhen Zheng","raw_affiliation_strings":["Monash University","Department of Data Science and AI, Faculty of IT, Monash University, Australia"],"affiliations":[{"raw_affiliation_string":"Monash University","institution_ids":["https://openalex.org/I2801239119","https://openalex.org/I56590836"]},{"raw_affiliation_string":"Department of Data Science and AI, Faculty of IT, Monash University, Australia","institution_ids":["https://openalex.org/I56590836"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017943466","display_name":"Yuan-Fang Li","orcid":"https://orcid.org/0000-0003-4651-2821"},"institutions":[{"id":"https://openalex.org/I56590836","display_name":"Monash University","ror":"https://ror.org/02bfwt286","country_code":"AU","type":"education","lineage":["https://openalex.org/I56590836"]},{"id":"https://openalex.org/I2801239119","display_name":"Australian Regenerative Medicine Institute","ror":"https://ror.org/02qa5kg76","country_code":"AU","type":"facility","lineage":["https://openalex.org/I2801037857","https://openalex.org/I2801239119","https://openalex.org/I56590836"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yuan-Fang Li","raw_affiliation_strings":["Monash University","Department of Data Science and AI, Faculty of IT, Monash University, Australia"],"affiliations":[{"raw_affiliation_string":"Monash University","institution_ids":["https://openalex.org/I2801239119","https://openalex.org/I56590836"]},{"raw_affiliation_string":"Department of Data Science and AI, Faculty of IT, Monash University, Australia","institution_ids":["https://openalex.org/I56590836"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030222911","display_name":"Chen Gong","orcid":"https://orcid.org/0000-0002-4092-9856"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen Gong","raw_affiliation_strings":["Nanjing University of Science and Technology","School of Computer Science and Engineering, Nanjing University of Science and Technology, China"],"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology","institution_ids":["https://openalex.org/I36399199"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085319576","display_name":"Chuan Zhou","orcid":"https://orcid.org/0000-0001-9958-8673"},"institutions":[{"id":"https://openalex.org/I4210120485","display_name":"Academy of Mathematics and Systems Science","ror":"https://ror.org/02jkmyk67","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210120485"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuan Zhou","raw_affiliation_strings":["Chinese Academy of Sciences","Academy of Mathematics and Systems Science, Chinese Academy of Sciences, China"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]},{"raw_affiliation_string":"Academy of Mathematics and Systems Science, Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I4210120485","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008056593","display_name":"Shirui Pan","orcid":"https://orcid.org/0000-0003-0794-527X"},"institutions":[{"id":"https://openalex.org/I56590836","display_name":"Monash University","ror":"https://ror.org/02bfwt286","country_code":"AU","type":"education","lineage":["https://openalex.org/I56590836"]},{"id":"https://openalex.org/I2801239119","display_name":"Australian Regenerative Medicine Institute","ror":"https://ror.org/02qa5kg76","country_code":"AU","type":"facility","lineage":["https://openalex.org/I2801037857","https://openalex.org/I2801239119","https://openalex.org/I56590836"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Shirui Pan","raw_affiliation_strings":["Monash University","Department of Data Science and AI, Faculty of IT, Monash University, Australia"],"affiliations":[{"raw_affiliation_string":"Monash University","institution_ids":["https://openalex.org/I2801239119","https://openalex.org/I56590836"]},{"raw_affiliation_string":"Department of Data Science and AI, Faculty of IT, Monash University, Australia","institution_ids":["https://openalex.org/I56590836"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5101484129"],"corresponding_institution_ids":["https://openalex.org/I2801239119","https://openalex.org/I56590836"],"apc_list":null,"apc_paid":null,"fwci":14.0809,"has_fulltext":false,"cited_by_count":136,"citation_normalized_percentile":{"value":0.99132169,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1477","last_page":"1483"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9983999729156494,"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":0.9983999729156494,"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":0.7951445579528809},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6374062299728394},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5978059768676758},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5470803380012512},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5335408449172974},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.44541433453559875},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4394146800041199},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.41126903891563416},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.32305675745010376}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7951445579528809},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6374062299728394},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5978059768676758},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5470803380012512},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5335408449172974},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.44541433453559875},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4394146800041199},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.41126903891563416},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.32305675745010376},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.24963/ijcai.2021/204","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2021/204","pdf_url":"https://www.ijcai.org/proceedings/2021/0204.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},{"id":"pmh:oai:monash.edu:publications/90eb714a-1d72-436f-85c6-979f0b29c5a9","is_oa":true,"landing_page_url":"https://research.monash.edu/en/publications/90eb714a-1d72-436f-85c6-979f0b29c5a9","pdf_url":null,"source":{"id":"https://openalex.org/S4306402625","display_name":"Monash University Research Portal (Monash University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I56590836","host_organization_name":"Monash University","host_organization_lineage":["https://openalex.org/I56590836"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Jin, M, Zheng, Y, Li, Y-F, Gong, C, Zhou, C & Pan, S 2021, Multi-scale contrastive siamese networks for self-supervised graph representation learning. in Z-H Zhou (ed.), Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence. IJCAI International Joint Conference on Artificial Intelligence, Association for the Advancement of Artificial Intelligence (AAAI), Marina del Rey CA USA, pp. 1477-1483, International Joint Conference on Artificial Intelligence 2021, Montreal, Quebec, Canada, 19/08/21. https://doi.org/10.24963/ijcai.2021/204","raw_type":"contributionToPeriodical"},{"id":"pmh:oai:research-repository.griffith.edu.au:10072/416725","is_oa":false,"landing_page_url":"http://hdl.handle.net/10072/416725","pdf_url":null,"source":{"id":"https://openalex.org/S4306402548","display_name":"Griffith Research Online (Griffith University, Queensland, Australia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I11701301","host_organization_name":"Griffith University","host_organization_lineage":["https://openalex.org/I11701301"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference output"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2021/204","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2021/204","pdf_url":"https://www.ijcai.org/proceedings/2021/0204.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3190214286.pdf","grobid_xml":"https://content.openalex.org/works/W3190214286.grobid-xml"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W2127589108","https://openalex.org/W2139823104","https://openalex.org/W2145287260","https://openalex.org/W2154851992","https://openalex.org/W2887997457","https://openalex.org/W2900470550","https://openalex.org/W2916106175","https://openalex.org/W2963312446","https://openalex.org/W2964015378","https://openalex.org/W2964321699","https://openalex.org/W2964420626","https://openalex.org/W3005680577","https://openalex.org/W3012816161","https://openalex.org/W3033039844","https://openalex.org/W3034693603","https://openalex.org/W3035060554","https://openalex.org/W3095602948","https://openalex.org/W3108655343","https://openalex.org/W3108949087","https://openalex.org/W3173292968","https://openalex.org/W4288088467","https://openalex.org/W4288275971","https://openalex.org/W4294558607","https://openalex.org/W4297571622","https://openalex.org/W4297733535","https://openalex.org/W4297808394","https://openalex.org/W4322614756"],"related_works":["https://openalex.org/W2062195135","https://openalex.org/W2795079307","https://openalex.org/W2793058541","https://openalex.org/W3118638206","https://openalex.org/W1983629434","https://openalex.org/W4324271173","https://openalex.org/W1588041347","https://openalex.org/W4285218279","https://openalex.org/W4386136067","https://openalex.org/W4286858940"],"abstract_inverted_index":{"Graph":[0],"representation":[1,16,41],"learning":[2,17,35],"plays":[3],"a":[4,45],"vital":[5],"role":[6],"in":[7,39,49],"processing":[8],"graph-structured":[9],"data.":[10],"However,":[11],"prior":[12],"arts":[13],"on":[14,20,76,114],"graph":[15,33,74],"heavily":[18],"rely":[19],"labeling":[21],"information.":[22],"To":[23,103],"overcome":[24],"this":[25,50],"problem,":[26],"inspired":[27],"by":[28,56,132],"the":[29,72,93,105],"recent":[30],"success":[31],"of":[32,107],"contrastive":[34,62],"and":[36,78,88,101],"Siamese":[37,58],"networks":[38],"visual":[40],"learning,":[42],"we":[43,65,82,110],"propose":[44],"novel":[46],"self-supervised":[47],"approach":[48],"paper":[51],"to":[52,91],"learn":[53],"node":[54,96],"representations":[55,97],"enhancing":[57],"self-distillation":[59],"with":[60],"multi-scale":[61],"learning.":[63],"Specifically,":[64],"first":[66],"generate":[67],"two":[68,84],"augmented":[69],"views":[70,100],"from":[71],"input":[73],"based":[75],"local":[77],"global":[79],"perspectives.":[80],"Then,":[81],"employ":[83],"objectives":[85],"called":[86],"cross-view":[87],"cross-network":[89],"contrastiveness":[90],"maximize":[92],"agreement":[94],"between":[95],"across":[98],"different":[99],"networks.":[102],"demonstrate":[104],"effectiveness":[106],"our":[108],"approach,":[109],"perform":[111],"empirical":[112],"experiments":[113],"five":[115],"real-world":[116],"datasets.":[117],"Our":[118],"method":[119],"not":[120],"only":[121],"achieves":[122],"new":[123],"state-of-the-art":[124],"results":[125],"but":[126],"also":[127],"surpasses":[128],"some":[129],"semi-supervised":[130],"counterparts":[131],"large":[133],"margins.":[134],"Code":[135],"is":[136],"made":[137],"available":[138],"at":[139],"https://github.com/GRAND-Lab/MERIT":[140]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":33},{"year":2024,"cited_by_count":28},{"year":2023,"cited_by_count":47},{"year":2022,"cited_by_count":17},{"year":2021,"cited_by_count":8}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}