{"id":"https://openalex.org/W2807630841","doi":"https://doi.org/10.48550/arxiv.1806.02978","title":"JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets","display_name":"JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets","publication_year":2018,"publication_date":"2018-06-08","ids":{"openalex":"https://openalex.org/W2807630841","doi":"https://doi.org/10.48550/arxiv.1806.02978","mag":"2807630841"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:1806.02978","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1806.02978","pdf_url":"https://arxiv.org/pdf/1806.02978","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1806.02978","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5023417820","display_name":"Yunchen Pu","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210114444","display_name":"Meta (United States)","ror":"https://ror.org/01zbnvs85","country_code":"US","type":"company","lineage":["https://openalex.org/I4210114444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pu, Yunchen","raw_affiliation_strings":["FACEBOOK, INC.,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"FACEBOOK, INC.,","institution_ids":["https://openalex.org/I4210114444"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Dai, Shuyang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dai, Shuyang","raw_affiliation_strings":["Duke University#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Duke University#TAB#","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066666034","display_name":"Zhe Gan","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gan, Zhe","raw_affiliation_strings":["Microsoft, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090949258","display_name":"Weiyao Wang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wang, Weiyao","raw_affiliation_strings":["Duke University#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Duke University#TAB#","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031220156","display_name":"Guoyin Wang","orcid":"https://orcid.org/0000-0002-8521-5232","observed_orcids":["https://orcid.org/0000-0002-8521-5232","https://orcid.org/0000-0003-1954-4174"]},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wang, Guoyin","raw_affiliation_strings":["Duke University#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Duke University#TAB#","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101959000","display_name":"Yizhe Zhang","orcid":"https://orcid.org/0000-0002-9599-7995","observed_orcids":["https://orcid.org/0000-0002-9599-7995"]},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhang, Yizhe","raw_affiliation_strings":["Microsoft, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056639842","display_name":"Ricardo Henao","orcid":"https://orcid.org/0000-0003-4980-845X","observed_orcids":["https://orcid.org/0000-0003-4980-845X"]},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Henao, Ricardo","raw_affiliation_strings":["Duke University#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Duke University#TAB#","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016448581","display_name":"Lawrence Carin","orcid":"https://orcid.org/0000-0001-6277-7948","observed_orcids":["https://orcid.org/0000-0001-6277-7948"]},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Carin, Lawrence","raw_affiliation_strings":["Duke University#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Duke University#TAB#","institution_ids":["https://openalex.org/I170897317"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":28,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4151","last_page":"4160"},"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":0.986299991607666,"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":0.986299991607666,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.00430000014603138,"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/T10320","display_name":"Neural Networks and Applications","score":0.0013000000035390258,"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/generative-adversarial-networks","display_name":"generative adversarial networks","score":0.8700000047683716},{"id":"https://openalex.org/keywords/multi-domain-data","display_name":"multi-domain data","score":0.6980000138282776},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"domain adaptation","score":0.3100000023841858}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.7491450905799866},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.7322009801864624},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.7223652601242065},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.6385304927825928},{"id":"https://openalex.org/C18653775","wikidata":"https://www.wikidata.org/wiki/Q1333358","display_name":"Joint probability distribution","level":2,"score":0.5670000314712524},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5497029423713684},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.522528886795044},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48944488167762756},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20518437027931213},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.16459038853645325},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.060832679271698},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.04752698540687561},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:arXiv.org:1806.02978","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1806.02978","pdf_url":"https://arxiv.org/pdf/1806.02978","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.1806.02978","doi":"https://doi.org/10.48550/arxiv.1806.02978","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1806.02978","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},{"id":"mag:2963484149","doi":null,"is_oa":false,"landing_page_url":"http://proceedings.mlr.press/v80/pu18a/pu18a.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306419644","display_name":"International Conference on Machine Learning","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"International Conference on Machine Learning","raw_type":null}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1806.02978","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1806.02978","pdf_url":"https://arxiv.org/pdf/1806.02978","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320306084","display_name":"U.S. Department of Energy","ror":"https://ror.org/01bj3aw27"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"},{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2807630841.pdf","grobid_xml":"https://content.openalex.org/works/W2807630841.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W14333344","https://openalex.org/W1522301498","https://openalex.org/W1901129140","https://openalex.org/W2093848332","https://openalex.org/W2099471712","https://openalex.org/W2125389028","https://openalex.org/W2136189984","https://openalex.org/W2173520492","https://openalex.org/W2202109488","https://openalex.org/W2411541852","https://openalex.org/W2412320034","https://openalex.org/W2471149695","https://openalex.org/W2519536754","https://openalex.org/W2527569769","https://openalex.org/W2552611751","https://openalex.org/W2564591810","https://openalex.org/W2579277680","https://openalex.org/W2596763562","https://openalex.org/W2598581049","https://openalex.org/W2625357353","https://openalex.org/W2951004968","https://openalex.org/W2953139137","https://openalex.org/W2962793481","https://openalex.org/W2962798930","https://openalex.org/W2963444790","https://openalex.org/W2963474063","https://openalex.org/W2963592272","https://openalex.org/W2963966654","https://openalex.org/W2964025273","https://openalex.org/W2964268978"],"related_works":["https://openalex.org/W2471149695","https://openalex.org/W2809129535","https://openalex.org/W2798170780","https://openalex.org/W2945839914","https://openalex.org/W2963474063","https://openalex.org/W2948770746","https://openalex.org/W4391692627","https://openalex.org/W2982183480","https://openalex.org/W4308613813","https://openalex.org/W2963592272"],"abstract_inverted_index":{"A":[0],"new":[1],"generative":[2],"adversarial":[3,76],"network":[4],"is":[5,36],"developed":[6],"for":[7,115,123],"joint":[8,28,109,116],"distribution":[9,29],"matching.":[10],"Distinct":[11],"from":[12,42,53,90,97,106],"most":[13],"existing":[14],"approaches,":[15],"that":[16],"only":[17],"learn":[18,26],"conditional":[19,43,93],"distributions,":[20],"the":[21,46,54,83,91,107],"proposed":[22,61,84],"model":[23],"aims":[24],"to":[25,40,51],"a":[27,68,79,98],"of":[30,56,64,88,100,118],"multiple":[31,65],"random":[32,101],"variables":[33],"(domains).":[34],"This":[35],"achieved":[37],"by":[38],"learning":[39,50],"sample":[41,52],"distributions":[44],"between":[45],"domains,":[47,120],"while":[48],"simultaneously":[49],"marginals":[55],"each":[57],"individual":[58],"domain.":[59],"The":[60],"framework":[62,85],"consists":[63],"generators":[66],"and":[67],"single":[69],"softmax-based":[70],"critic,":[71],"all":[72],"jointly":[73],"trained":[74],"via":[75],"learning.":[77],"From":[78],"simple":[80],"noise":[81],"source,":[82],"allows":[86],"synthesis":[87],"draws":[89,94,105],"marginals,":[92],"given":[95],"observations":[96],"subset":[99],"variables,":[102],"or":[103],"complete":[104],"full":[108],"distribution.":[110],"Most":[111],"examples":[112,122],"considered":[113],"are":[114],"analysis":[117],"two":[119],"with":[121],"three":[124],"domains":[125],"also":[126],"presented.":[127]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":6}],"updated_date":"2026-11-05T12:25:35.769452","created_date":"2018-06-13T00:00:00"}
