{"id":"https://openalex.org/W3016305693","doi":"https://doi.org/10.1109/icaiic48513.2020.9065044","title":"A Survey of Missing Data Imputation Using Generative Adversarial Networks","display_name":"A Survey of Missing Data Imputation Using Generative Adversarial Networks","publication_year":2020,"publication_date":"2020-02-01","ids":{"openalex":"https://openalex.org/W3016305693","doi":"https://doi.org/10.1109/icaiic48513.2020.9065044","mag":"3016305693"},"language":"en","primary_location":{"id":"doi:10.1109/icaiic48513.2020.9065044","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaiic48513.2020.9065044","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","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/A5109464360","display_name":"Jaeyoon Kim","orcid":"https://orcid.org/0000-0002-4692-8467"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Jaeyoon Kim","raw_affiliation_strings":["School of Electrical Engineering, Korea University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Korea University, Seoul, South Korea","institution_ids":["https://openalex.org/I197347611"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000505469","display_name":"Donghyun Tae","orcid":null},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Donghyun Tae","raw_affiliation_strings":["School of Electrical Engineering, Korea University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Korea University, Seoul, South Korea","institution_ids":["https://openalex.org/I197347611"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069534195","display_name":"Junhee Seok","orcid":"https://orcid.org/0000-0002-6475-8457"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Junhee Seok","raw_affiliation_strings":["School of Electrical Engineering, Korea University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Korea University, Seoul, South Korea","institution_ids":["https://openalex.org/I197347611"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5109464360"],"corresponding_institution_ids":["https://openalex.org/I197347611"],"apc_list":null,"apc_paid":null,"fwci":3.1405,"has_fulltext":false,"cited_by_count":45,"citation_normalized_percentile":{"value":0.93193535,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"454","last_page":"456"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9994999766349792,"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"}},"topics":[{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9994999766349792,"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/T11448","display_name":"Face recognition and analysis","score":0.9965000152587891,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9958000183105469,"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/discriminator","display_name":"Discriminator","score":0.9139950275421143},{"id":"https://openalex.org/keywords/imputation","display_name":"Imputation (statistics)","score":0.850132405757904},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7584284543991089},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.7304757833480835},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.7105357050895691},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.6831443309783936},{"id":"https://openalex.org/keywords/generative-adversarial-network","display_name":"Generative adversarial network","score":0.5755183696746826},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5537207126617432},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.5160459876060486},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4993166923522949},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.47050684690475464},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.44864189624786377},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44825834035873413},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3667997121810913}],"concepts":[{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.9139950275421143},{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.850132405757904},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7584284543991089},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.7304757833480835},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.7105357050895691},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.6831443309783936},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.5755183696746826},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5537207126617432},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.5160459876060486},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4993166923522949},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.47050684690475464},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44864189624786377},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44825834035873413},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3667997121810913},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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},{"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/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icaiic48513.2020.9065044","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaiic48513.2020.9065044","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.75}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W2099471712","https://openalex.org/W2738588019","https://openalex.org/W2803403013","https://openalex.org/W2962932373","https://openalex.org/W2982763192","https://openalex.org/W3043547428","https://openalex.org/W4288558759","https://openalex.org/W4288562516","https://openalex.org/W4320013936","https://openalex.org/W6751145664"],"related_works":["https://openalex.org/W2181530120","https://openalex.org/W4211215373","https://openalex.org/W2024529227","https://openalex.org/W1574575415","https://openalex.org/W3144172081","https://openalex.org/W3179858851","https://openalex.org/W3028371478","https://openalex.org/W2081476516","https://openalex.org/W2581984549","https://openalex.org/W3123177881"],"abstract_inverted_index":{"Recently,":[0],"many":[1],"deep":[2],"learning":[3],"models":[4,17,73],"for":[5,74],"missing":[6,75],"data":[7,27,76],"imputation":[8],"have":[9,60],"been":[10,61],"studied.":[11],"One":[12],"of":[13,42],"the":[14,39],"most":[15],"popular":[16],"is":[18],"Generative":[19],"Adversarial":[20],"Networks":[21],"(GANs),":[22],"which":[23],"generate":[24],"plausible":[25],"fake":[26],"through":[28],"adversarial":[29],"training.":[30],"In":[31],"this":[32],"paper,":[33],"we":[34,55,67],"take":[35],"a":[36,43,46],"look":[37],"at":[38],"architecture,":[40],"objective":[41],"generator":[44],"and":[45,50],"discriminator,":[47],"training":[48],"method":[49],"loss":[51],"function.":[52],"After":[53],"that,":[54],"can":[56,68],"see":[57],"what":[58],"improvements":[59],"made":[62],"to":[63],"each":[64],"model.":[65],"Moreover,":[66],"easily":[69],"compare":[70],"several":[71],"GAN-based":[72],"imputation.":[77]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":15},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":4}],"updated_date":"2026-04-18T07:56:08.524223","created_date":"2025-10-10T00:00:00"}