{"id":"https://openalex.org/W4412623136","doi":"https://doi.org/10.1109/tkde.2025.3592640","title":"GI-Graph: A Generative Invariant Graph Learning Scheme Towards Out-of-Distribution Generalization","display_name":"GI-Graph: A Generative Invariant Graph Learning Scheme Towards Out-of-Distribution Generalization","publication_year":2025,"publication_date":"2025-07-24","ids":{"openalex":"https://openalex.org/W4412623136","doi":"https://doi.org/10.1109/tkde.2025.3592640"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2025.3592640","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2025.3592640","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-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/A5102748712","display_name":"Sanfeng Zhang","orcid":"https://orcid.org/0000-0001-6626-0487"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sanfeng Zhang","raw_affiliation_strings":["School of Cyber Science and Engineering, Southeast University, Nanjing, China","School of Cyber Science and Engineering, Southeast University and Key Laboratory of Computer Network and Information Integration (Southeast University), Ministry of Education, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0001-6626-0487","affiliations":[{"raw_affiliation_string":"School of Cyber Science and Engineering, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"School of Cyber Science and Engineering, Southeast University and Key Laboratory of Computer Network and Information Integration (Southeast University), Ministry of Education, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100395656","display_name":"Xinyi Liu","orcid":"https://orcid.org/0000-0001-8864-0528"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyi Liu","raw_affiliation_strings":["School of Cyber Science and Engineering, Southeast University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Cyber Science and Engineering, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zihao Qi","orcid":"https://orcid.org/0009-0009-0606-0809"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zihao Qi","raw_affiliation_strings":["School of Cyber Science and Engineering, Southeast University, Nanjing, China"],"raw_orcid":"https://orcid.org/0009-0009-0606-0809","affiliations":[{"raw_affiliation_string":"School of Cyber Science and Engineering, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032565611","display_name":"Xingchen Yan","orcid":"https://orcid.org/0000-0003-3704-4739"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingchen Yan","raw_affiliation_strings":["School of Cyber Science and Engineering, Southeast University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Cyber Science and Engineering, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075665882","display_name":"Yang Wang","orcid":"https://orcid.org/0000-0002-4125-9436"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wang Yang","raw_affiliation_strings":["School of Cyber Science and Engineering, Southeast University, Nanjing, China","School of Cyber Science and Engineering, Southeast University and Key Laboratory of Computer Network and Information Integration (Southeast University), Ministry of Education, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Cyber Science and Engineering, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"School of Cyber Science and Engineering, Southeast University and Key Laboratory of Computer Network and Information Integration (Southeast University), Ministry of Education, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I76569877"],"apc_list":null,"apc_paid":null,"fwci":3.3016,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.92555698,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":"37","issue":"10","first_page":"5934","last_page":"5947"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9836000204086304,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9836000204086304,"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/T10057","display_name":"Face and Expression Recognition","score":0.9599999785423279,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9505000114440918,"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":0.6851503849029541},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5316202044487},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.507164716720581},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.457337886095047},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.45110028982162476},{"id":"https://openalex.org/keywords/voltage-graph","display_name":"Voltage graph","score":0.4244886338710785},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33024758100509644},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23845893144607544},{"id":"https://openalex.org/keywords/line-graph","display_name":"Line graph","score":0.22373643517494202}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6851503849029541},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5316202044487},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.507164716720581},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.457337886095047},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.45110028982162476},{"id":"https://openalex.org/C22149727","wikidata":"https://www.wikidata.org/wiki/Q7940747","display_name":"Voltage graph","level":4,"score":0.4244886338710785},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33024758100509644},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23845893144607544},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"score":0.22373643517494202},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2025.3592640","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2025.3592640","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W2594183968","https://openalex.org/W2985576648","https://openalex.org/W3042856524","https://openalex.org/W3048964647","https://openalex.org/W3087257704","https://openalex.org/W3095992020","https://openalex.org/W3107119534","https://openalex.org/W3119242082","https://openalex.org/W4200635484","https://openalex.org/W4239944110","https://openalex.org/W4248633940","https://openalex.org/W4282004119","https://openalex.org/W4382458099","https://openalex.org/W4386072181","https://openalex.org/W4387250121","https://openalex.org/W4391568820","https://openalex.org/W4393147936","https://openalex.org/W4393972734","https://openalex.org/W4404781529"],"related_works":["https://openalex.org/W2380075625","https://openalex.org/W4390718435","https://openalex.org/W4390549206","https://openalex.org/W3137171911","https://openalex.org/W3119680273","https://openalex.org/W4366828432","https://openalex.org/W3154113024","https://openalex.org/W2115935649","https://openalex.org/W4312722798","https://openalex.org/W2904630684"],"abstract_inverted_index":{"When":[0],"distribution":[1],"shifts":[2],"occur":[3],"between":[4],"testing":[5],"and":[6,55,70,74,101,116,128,145],"training":[7],"graph":[8,17,35,64,174,178],"data,":[9],"out-of-distribution":[10],"(OOD)":[11],"samples":[12],"undermine":[13],"the":[14,92,124,134,152,168,171],"performance":[15],"of":[16,26,42,118,138,170],"neural":[18],"networks":[19],"(GNNs).":[20],"To":[21],"improve":[22,133],"adaptive":[23],"OOD":[24,93,135,179],"generalization":[25,136],"GNNs,":[27],"this":[28],"paper":[29,166],"introduces":[30],"a":[31,63,83],"novel":[32],"generative":[33,47,51,172],"invariant":[34,52,72,109,129,143,173],"learning":[36,175],"framework,":[37],"named":[38],"GI-Graph.":[39],"It":[40],"consists":[41],"four":[43],"modules:":[44],"subgraph":[45,49,53,60,69,73,127,130],"extractor,":[46],"environment":[48,68,89,126],"augmentation,":[50],"learning,":[54,100],"query":[56,79],"feedback":[57],"module.":[58],"The":[59],"extractor":[61],"decomposes":[62],"sample":[65],"into":[66],"an":[67,71],"improves":[75],"extraction":[76],"accuracy":[77],"through":[78],"feedback.":[80],"GI-Graph":[81,105,158],"uses":[82],"diffusion":[84,97],"model":[85],"to":[86,159,162],"generate":[87],"diverse":[88],"subgraphs,":[90],"augmenting":[91],"data.":[94],"By":[95],"combining":[96],"models,":[98],"contrastive":[99,153],"attribute":[102],"prediction":[103],"networks,":[104],"also":[106],"generates":[107],"augmented":[108],"subgraphs":[110],"with":[111],"significant":[112],"identically":[113],"distributed":[114],"features":[115,144],"consistency":[117,148],"labels.":[119],"Experimental":[120],"results":[121],"demonstrate":[122],"that":[123],"controllable":[125],"augmentation":[131],"effectively":[132],"capability":[137],"GI-Graph,":[139],"especially":[140],"in":[141,177],"capturing":[142],"maintaining":[146],"category":[147],"across":[149],"environments.":[150,164],"Additionally,":[151],"learning-based":[154],"finetuning":[155],"method":[156],"enables":[157],"quickly":[160],"adapt":[161],"evolving":[163],"This":[165],"verifies":[167],"effectiveness":[169],"scheme":[176],"generalization.":[180]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}