{"id":"https://openalex.org/W4414856635","doi":"https://doi.org/10.1109/tnnls.2025.3613549","title":"Learning Counterfactual Fair Representation Under Covariate Shift via Reflux","display_name":"Learning Counterfactual Fair Representation Under Covariate Shift via Reflux","publication_year":2025,"publication_date":"2025-10-06","ids":{"openalex":"https://openalex.org/W4414856635","doi":"https://doi.org/10.1109/tnnls.2025.3613549","pmid":"https://pubmed.ncbi.nlm.nih.gov/41052178"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2025.3613549","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2025.3613549","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5113091349","display_name":"Yiliang Xia","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiliang Xia","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0009-2792-3239","affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108046737","display_name":"Xiaohang Zhang","orcid":"https://orcid.org/0000-0002-5315-8712"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaohang Zhang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-5315-8712","affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016933558","display_name":"Zhengren Li","orcid":"https://orcid.org/0000-0003-2908-2233"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhengren Li","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-2908-2233","affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13762066,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"37","issue":"2","first_page":"878","last_page":"892"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9363999962806702,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9363999962806702,"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/counterfactual-thinking","display_name":"Counterfactual thinking","score":0.8838000297546387},{"id":"https://openalex.org/keywords/covariate","display_name":"Covariate","score":0.6255999803543091},{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.5195000171661377},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4359999895095825},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.35899999737739563},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.3276999890804291}],"concepts":[{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.8838000297546387},{"id":"https://openalex.org/C119043178","wikidata":"https://www.wikidata.org/wiki/Q320723","display_name":"Covariate","level":2,"score":0.6255999803543091},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5424000024795532},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.5195000171661377},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.4359999895095825},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4359999895095825},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3930000066757202},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.35899999737739563},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3418999910354614},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.3276999890804291},{"id":"https://openalex.org/C37381756","wikidata":"https://www.wikidata.org/wiki/Q20203288","display_name":"Representativeness heuristic","level":2,"score":0.32580000162124634},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.31130000948905945},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.3109000027179718},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30059999227523804},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.28029999136924744},{"id":"https://openalex.org/C110893760","wikidata":"https://www.wikidata.org/wiki/Q3115590","display_name":"Named graph","level":5,"score":0.27630001306533813},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.25040000677108765}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2025.3613549","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2025.3613549","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:41052178","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41052178","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3245652008","display_name":null,"funder_award_id":"72271034","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1961345416","https://openalex.org/W2014352947","https://openalex.org/W2034368206","https://openalex.org/W2143891888","https://openalex.org/W2155183960","https://openalex.org/W2166944917","https://openalex.org/W2550080458","https://openalex.org/W2959197226","https://openalex.org/W2962833164","https://openalex.org/W2963331808","https://openalex.org/W2966613548","https://openalex.org/W3082738012","https://openalex.org/W3089471696","https://openalex.org/W3110081891","https://openalex.org/W3124833072","https://openalex.org/W3176952330","https://openalex.org/W4213199213","https://openalex.org/W4251742697","https://openalex.org/W4282843632","https://openalex.org/W4291804750","https://openalex.org/W4311415873","https://openalex.org/W4364302664","https://openalex.org/W4366083537","https://openalex.org/W4372260129","https://openalex.org/W4378419993","https://openalex.org/W4388854885","https://openalex.org/W4399267674","https://openalex.org/W4404371500","https://openalex.org/W4406729824"],"related_works":[],"abstract_inverted_index":{"Recent":[0],"advances":[1],"in":[2],"counterfactual":[3,18,72,82,102,130],"fairness":[4,11,16,29,152,171],"have":[5],"shifted":[6],"focus":[7],"from":[8],"flawed":[9],"group":[10],"metrics":[12],"to":[13,26,41,99,139,180],"ensuring":[14],"individual-level":[15],"through":[17],"reasoning.":[19],"However,":[20],"most":[21],"existing":[22,169],"approaches":[23],"remain":[24],"limited":[25,183],"in-processing":[27,170],"strategies-injecting":[28],"constraints":[30],"into":[31],"predictive":[32],"models-while":[33],"largely":[34],"overlooking":[35],"the":[36,49,59,71,89,96],"potential":[37],"of":[38,52,61,91],"data":[39],"preprocessing":[40],"mitigate":[42],"inherent":[43],"biases.":[44],"Moreover,":[45],"few":[46],"methods":[47],"address":[48],"critical":[50],"challenge":[51],"real-world":[53],"distribution":[54],"shift,":[55,108],"which":[56],"can":[57,164],"compromise":[58],"generalizability":[60],"fair":[62,86,103,141],"models":[63],"across":[64,143,160],"domains.":[65,144,161],"In":[66],"this":[67,94,178],"article,":[68],"we":[69,119,134],"propose":[70],"reflux":[73],"variational":[74],"autoencoder":[75],"(CRVAE),":[76],"a":[77,121,136],"novel":[78],"framework":[79,179],"for":[80],"generating":[81],"samples":[83],"and":[84,112,129,157],"learning":[85,105],"representations.":[87,131],"To":[88],"best":[90],"our":[92,149],"knowledge,":[93],"is":[95],"first":[97],"work":[98,174],"explicitly":[100],"consider":[101],"representation":[104],"under":[106],"covariate":[107,113],"enabling":[109],"both":[110],"single-domain":[111],"shift":[114],"prediction":[115],"tasks.":[116],"For":[117,132],"fairness,":[118],"introduce":[120],"Reflux":[122],"technique":[123],"that":[124,148],"enforces":[125],"consistency":[126],"between":[127],"factual":[128],"transferability,":[133],"incorporate":[135],"domain":[137],"discriminator":[138],"align":[140],"representations":[142],"Experimental":[145],"results":[146],"show":[147],"approach":[150],"improves":[151],"with":[153,168,182],"minimal":[154],"performance":[155],"loss":[156],"maintains":[158],"generalization":[159],"Furthermore,":[162],"CRVAE":[163],"be":[165],"flexibly":[166],"combined":[167],"methods.":[172],"Future":[173],"may":[175],"explore":[176],"extending":[177],"settings":[181],"causal":[184],"graph":[185],"knowledge.":[186]},"counts_by_year":[],"updated_date":"2026-02-07T06:11:34.122080","created_date":"2025-10-10T00:00:00"}