{"id":"https://openalex.org/W4391306859","doi":"https://doi.org/10.1109/smc53992.2023.10394476","title":"GeAE: GAE-Embedded Autoencoder Based Causal Representation for Robust Domain Adaptation","display_name":"GeAE: GAE-Embedded Autoencoder Based Causal Representation for Robust Domain Adaptation","publication_year":2023,"publication_date":"2023-10-01","ids":{"openalex":"https://openalex.org/W4391306859","doi":"https://doi.org/10.1109/smc53992.2023.10394476"},"language":"en","primary_location":{"id":"doi:10.1109/smc53992.2023.10394476","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc53992.2023.10394476","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-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&#x0027;an,China"],"affiliations":[{"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":"Jiang Ming","raw_affiliation_strings":["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&#x0027;an,China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"last","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":["University of Technology Sydney,Complex Adaptive Systems Lab,Sydney,Australia","Complex Adaptive Systems Lab, University of Technology Sydney, Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"University of Technology Sydney,Complex Adaptive Systems Lab,Sydney,Australia","institution_ids":["https://openalex.org/I114017466"]},{"raw_affiliation_string":"Complex Adaptive Systems Lab, University of Technology Sydney, Sydney, Australia","institution_ids":["https://openalex.org/I114017466"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5047500564"],"corresponding_institution_ids":["https://openalex.org/I17145004"],"apc_list":null,"apc_paid":null,"fwci":0.1748,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.59864641,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"3777","last_page":"3782"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9987000226974487,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9987000226974487,"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":0.9532219171524048},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.6864669322967529},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6663036346435547},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6247897148132324},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5380366444587708},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5049527287483215},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4855503737926483},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.4725567698478699},{"id":"https://openalex.org/keywords/causal-structure","display_name":"Causal structure","score":0.4684130549430847},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46232110261917114},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4560205936431885},{"id":"https://openalex.org/keywords/transfer-entropy","display_name":"Transfer entropy","score":0.43542835116386414},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3311341106891632},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.318805456161499},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3159499168395996},{"id":"https://openalex.org/keywords/principle-of-maximum-entropy","display_name":"Principle of maximum entropy","score":0.16599923372268677}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.9532219171524048},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.6864669322967529},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6663036346435547},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6247897148132324},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5380366444587708},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5049527287483215},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4855503737926483},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.4725567698478699},{"id":"https://openalex.org/C163504300","wikidata":"https://www.wikidata.org/wiki/Q2364925","display_name":"Causal structure","level":2,"score":0.4684130549430847},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46232110261917114},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4560205936431885},{"id":"https://openalex.org/C182049051","wikidata":"https://www.wikidata.org/wiki/Q17147155","display_name":"Transfer entropy","level":3,"score":0.43542835116386414},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3311341106891632},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.318805456161499},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3159499168395996},{"id":"https://openalex.org/C9679016","wikidata":"https://www.wikidata.org/wiki/Q1417473","display_name":"Principle of maximum entropy","level":2,"score":0.16599923372268677},{"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc53992.2023.10394476","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc53992.2023.10394476","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G492184777","display_name":null,"funder_award_id":"20182053023","funder_id":"https://openalex.org/F4320322857","funder_display_name":"Aeronautical Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320322857","display_name":"Aeronautical Science Foundation of China","ror":"https://ror.org/02wq41p38"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2525748243","https://openalex.org/W2611743072","https://openalex.org/W2798658180","https://openalex.org/W2952369555","https://openalex.org/W2963898943","https://openalex.org/W2980507899","https://openalex.org/W2987511773","https://openalex.org/W3101227657","https://openalex.org/W3206842362","https://openalex.org/W6726873649","https://openalex.org/W6754506371","https://openalex.org/W6761805307","https://openalex.org/W6770269537"],"related_works":["https://openalex.org/W2983142544","https://openalex.org/W2891059443","https://openalex.org/W4281663961","https://openalex.org/W3034688404","https://openalex.org/W3208888551","https://openalex.org/W4313561566","https://openalex.org/W3208386644","https://openalex.org/W4389832810","https://openalex.org/W4220682630","https://openalex.org/W3181622257"],"abstract_inverted_index":{"In":[0],"this":[1],"work,":[2],"we":[3],"study":[4],"the":[5,23,62,76,82,87,93,103,121,128],"unsupervised":[6],"robust":[7,49],"domain":[8,18,50],"adaptation":[9],"problem":[10],"where":[11],"only":[12],"a":[13,33,65,72,98],"single":[14],"well":[15,80],"labeled":[16],"source":[17],"data":[19,63],"is":[20,40],"available":[21],"during":[22],"learning":[24,68],"process.":[25],"A":[26],"new":[27],"causal":[28,58,66,83,108],"representation":[29],"method":[30,54],"based":[31],"on":[32,112],"Graph":[34],"autoen-coder":[35],"embedded":[36],"AutoEncoder,":[37],"named":[38],"GeAE,":[39],"introduced":[41],"to":[42,71,101],"learn":[43],"invariant":[44],"representations":[45],"across":[46],"domains":[47],"for":[48],"adaption.":[51],"The":[52],"proposed":[53],"can":[55],"handle":[56],"nonlinear":[57],"relations":[59],"included":[60],"in":[61,92,97,125],"by":[64],"structure":[67,84],"process":[69],"similar":[70],"graph":[73],"autoencoder.":[74],"Moreover,":[75],"cross-entropy":[77],"loss":[78,85,89],"as":[79,81],"and":[86,116],"reconstruction":[88],"are":[90],"incorporated":[91],"objective":[94],"function":[95],"designed":[96],"united":[99],"autoencoder":[100],"improve":[102],"quality":[104],"of":[105,123],"predictions":[106],"using":[107],"representations.":[109],"Experimental":[110],"results":[111],"one":[113],"generated":[114],"dataset":[115],"three":[117],"real-world":[118],"datasets":[119],"demonstrate":[120],"effectiveness":[122],"GeAE":[124],"comparison":[126],"with":[127],"state-of-the-art":[129],"methods.":[130]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
