{"id":"https://openalex.org/W4408071482","doi":"https://doi.org/10.1109/tkde.2025.3546607","title":"Learning Causal Representations Based on a GAE Embedded Autoencoder","display_name":"Learning Causal Representations Based on a GAE Embedded Autoencoder","publication_year":2025,"publication_date":"2025-02-28","ids":{"openalex":"https://openalex.org/W4408071482","doi":"https://doi.org/10.1109/tkde.2025.3546607"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2025.3546607","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2025.3546607","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/A5047500564","display_name":"Kuang Zhou","orcid":"https://orcid.org/0000-0002-7278-3652"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Kuang Zhou","raw_affiliation_strings":["School of Mathematics and Statistics, Northwestern Polytechnical University, Xi&#x2019;an, China","School of mathematics and statistics, Northwestern Polytechnical University, Xi&#x0027;an, China"],"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Northwestern Polytechnical University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"School of mathematics and statistics, Northwestern Polytechnical University, Xi&#x0027;an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022001222","display_name":"Ming Jiang","orcid":"https://orcid.org/0000-0001-6102-8785"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Jiang","raw_affiliation_strings":["School of Mathematics and Statistics, Northwestern Polytechnical University, Xi&#x2019;an, China","School of mathematics and statistics, Northwestern Polytechnical University, Xi&#x0027;an, China"],"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Northwestern Polytechnical University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"School of mathematics and statistics, Northwestern Polytechnical University, Xi&#x0027;an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083181106","display_name":"Bogdan Gabry\u015b","orcid":"https://orcid.org/0000-0002-0790-2846"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Bogdan Gabrys","raw_affiliation_strings":["Complex Adaptive Systems Lab, University of Technology Sydney, Ultimo, NSW, Australia","Complex Adaptive Systems Lab, University of Technology Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"Complex Adaptive Systems Lab, University of Technology Sydney, Ultimo, NSW, Australia","institution_ids":["https://openalex.org/I114017466"]},{"raw_affiliation_string":"Complex Adaptive Systems Lab, University of Technology Sydney, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101467338","display_name":"Yong Xu","orcid":"https://orcid.org/0000-0003-4944-6890"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Xu","raw_affiliation_strings":["School of Mathematics and Statistics, Northwestern Polytechnical University, Xi&#x2019;an, China","School of mathematics and statistics, Northwestern Polytechnical University, Xi&#x0027;an, China"],"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Northwestern Polytechnical University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"School of mathematics and statistics, Northwestern Polytechnical University, Xi&#x0027;an, China","institution_ids":["https://openalex.org/I17145004"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5047500564"],"corresponding_institution_ids":["https://openalex.org/I17145004"],"apc_list":null,"apc_paid":null,"fwci":15.6592,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.9853402,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"37","issue":"6","first_page":"3472","last_page":"3484"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.8209999799728394,"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/T10320","display_name":"Neural Networks and Applications","score":0.8209999799728394,"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/autoencoder","display_name":"Autoencoder","score":0.7949039936065674},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7713512182235718},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4853626489639282},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.33012503385543823},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.2973487973213196}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.7949039936065674},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7713512182235718},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4853626489639282},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.33012503385543823},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2973487973213196}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2025.3546607","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2025.3546607","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":[{"display_name":"Reduced inequalities","score":0.44999998807907104,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G3253789004","display_name":null,"funder_award_id":"61701409","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7901961723","display_name":null,"funder_award_id":"92371101","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":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":59,"referenced_works":["https://openalex.org/W1920962657","https://openalex.org/W2087977130","https://openalex.org/W2112483442","https://openalex.org/W2115403315","https://openalex.org/W2122838776","https://openalex.org/W2143043751","https://openalex.org/W2154053567","https://openalex.org/W2165698076","https://openalex.org/W2171548678","https://openalex.org/W2207593006","https://openalex.org/W2466989778","https://openalex.org/W2525748243","https://openalex.org/W2798658180","https://openalex.org/W2803113114","https://openalex.org/W2884771968","https://openalex.org/W2894728917","https://openalex.org/W2963544905","https://openalex.org/W2963693396","https://openalex.org/W2963898943","https://openalex.org/W2980507899","https://openalex.org/W2990641522","https://openalex.org/W3004205097","https://openalex.org/W3033161486","https://openalex.org/W3039883906","https://openalex.org/W3091533194","https://openalex.org/W3101227657","https://openalex.org/W3107499124","https://openalex.org/W3119686825","https://openalex.org/W3131163951","https://openalex.org/W3133932964","https://openalex.org/W3199890178","https://openalex.org/W3202933889","https://openalex.org/W4221092700","https://openalex.org/W4250143236","https://openalex.org/W4282939914","https://openalex.org/W4285107695","https://openalex.org/W4288064774","https://openalex.org/W4299803032","https://openalex.org/W4303418564","https://openalex.org/W4310456609","https://openalex.org/W4312232143","https://openalex.org/W4313137733","https://openalex.org/W4316035539","https://openalex.org/W4318459969","https://openalex.org/W4364322759","https://openalex.org/W4376108212","https://openalex.org/W4381620595","https://openalex.org/W6606090912","https://openalex.org/W6636914306","https://openalex.org/W6637225622","https://openalex.org/W6678875967","https://openalex.org/W6683608245","https://openalex.org/W6683633756","https://openalex.org/W6726873649","https://openalex.org/W6754506371","https://openalex.org/W6761805307","https://openalex.org/W6770269537","https://openalex.org/W6785863445","https://openalex.org/W6790146069"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W3013693939","https://openalex.org/W2566616303","https://openalex.org/W2159052453","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W2803255133","https://openalex.org/W4220775285"],"abstract_inverted_index":{"Traditional":[0],"machine-learning":[1],"approaches":[2],"face":[3],"limitations":[4,87],"when":[5,88],"confronted":[6],"with":[7,45,93,204],"insufficient":[8],"data.":[9,145],"Transfer":[10],"learning":[11,25,129,156],"addresses":[12],"this":[13,98],"by":[14],"leveraging":[15],"knowledge":[16],"from":[17],"closely":[18],"related":[19],"domains.":[20,121],"The":[21,122],"key":[22],"in":[23,39,47,57,143,164,169],"transfer":[24],"is":[26,114],"to":[27,33,55,64,90,116,132,136],"find":[28],"a":[29,100,107,126,133,170],"transferable":[30],"feature":[31],"representation":[32,103],"enhance":[34],"cross-domain":[35,188],"classification":[36,189],"models.":[37],"However,":[38],"some":[40,42],"scenarios,":[41],"features":[43],"correlated":[44],"samples":[46],"the":[48,58,66,72,75,144,147,153,159,165,177,199,205],"source":[49],"domain":[50],"may":[51],"not":[52],"be":[53],"relevant":[54],"those":[56],"target.":[59],"Causal":[60],"inference":[61,84],"enables":[62],"us":[63],"uncover":[65],"underlying":[67],"patterns":[68],"and":[69,158,182,195],"mechanisms":[70],"within":[71],"data,":[73],"mitigating":[74],"impact":[76],"of":[77,179,201],"confounding":[78],"factors.":[79],"Nevertheless,":[80],"most":[81],"existing":[82],"causal":[83,95,102,127,140,154],"algorithms":[85],"have":[86],"applied":[89],"high-dimensional":[91,180],"datasets":[92,197],"nonlinear":[94,139],"relationships.":[96],"In":[97],"work,":[99],"new":[101],"method":[104,174],"based":[105],"on":[106,193],"Graph":[108],"autoencoder":[109],"embedded":[110],"AutoEncoder,":[111],"named":[112],"GeAE,":[113],"introduced":[115],"learn":[117],"invariant":[118],"representations":[119,186],"across":[120],"proposed":[123],"approach":[124],"employs":[125],"structure":[128,155],"module,":[130],"similar":[131],"graph":[134],"autoencoder,":[135],"account":[137],"for":[138,176,187],"relationships":[141],"present":[142],"Moreover,":[146],"cross-entropy":[148],"loss":[149,157,161],"as":[150,152],"well":[151],"reconstruction":[160],"are":[162],"incorporated":[163],"objective":[166],"function":[167],"designed":[168],"united":[171],"autoencoder.":[172],"This":[173],"allows":[175],"handling":[178],"data":[181],"can":[183],"provide":[184],"effective":[185],"tasks.":[190],"Experimental":[191],"results":[192],"generated":[194],"real-world":[196],"demonstrate":[198],"effectiveness":[200],"GeAE":[202],"compared":[203],"state-of-the-art":[206],"methods.":[207]},"counts_by_year":[{"year":2025,"cited_by_count":5}],"updated_date":"2025-12-28T23:10:05.387466","created_date":"2025-10-10T00:00:00"}
