{"id":"https://openalex.org/W3107893393","doi":"https://doi.org/10.1145/3397536.3422261","title":"COVID-GAN","display_name":"COVID-GAN","publication_year":2020,"publication_date":"2020-11-03","ids":{"openalex":"https://openalex.org/W3107893393","doi":"https://doi.org/10.1145/3397536.3422261","mag":"3107893393"},"language":"en","primary_location":{"id":"doi:10.1145/3397536.3422261","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3397536.3422261","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"},"type":"conference-paper","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/A5050161940","display_name":"Han Bao","orcid":"https://orcid.org/0000-0002-0109-8260"},"institutions":[{"id":"https://openalex.org/I126307644","display_name":"University of Iowa","ror":"https://ror.org/036jqmy94","country_code":"US","type":"education","lineage":["https://openalex.org/I126307644"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Han Bao","raw_affiliation_strings":["University of Iowa"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Iowa","institution_ids":["https://openalex.org/I126307644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086198510","display_name":"Xun Zhou","orcid":"https://orcid.org/0000-0003-4930-6572"},"institutions":[{"id":"https://openalex.org/I126307644","display_name":"University of Iowa","ror":"https://ror.org/036jqmy94","country_code":"US","type":"education","lineage":["https://openalex.org/I126307644"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xun Zhou","raw_affiliation_strings":["University of Iowa"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Iowa","institution_ids":["https://openalex.org/I126307644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074277827","display_name":"Yingxue Zhang","orcid":"https://orcid.org/0000-0002-0947-1875"},"institutions":[{"id":"https://openalex.org/I107077323","display_name":"Worcester Polytechnic Institute","ror":"https://ror.org/05ejpqr48","country_code":"US","type":"education","lineage":["https://openalex.org/I107077323"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yingxue Zhang","raw_affiliation_strings":["Worcester Polytechnic Institute"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Worcester Polytechnic Institute","institution_ids":["https://openalex.org/I107077323"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100630059","display_name":"Yanhua Li","orcid":"https://orcid.org/0000-0001-8972-503X"},"institutions":[{"id":"https://openalex.org/I107077323","display_name":"Worcester Polytechnic Institute","ror":"https://ror.org/05ejpqr48","country_code":"US","type":"education","lineage":["https://openalex.org/I107077323"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yanhua Li","raw_affiliation_strings":["Worcester Polytechnic Institute"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Worcester Polytechnic Institute","institution_ids":["https://openalex.org/I107077323"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049041437","display_name":"Yiqun Xie","orcid":"https://orcid.org/0000-0002-6439-1333"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yiqun Xie","raw_affiliation_strings":["University of Maryland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":33.2609,"has_fulltext":false,"cited_by_count":38,"citation_normalized_percentile":{"value":0.99794977,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"273","last_page":"282"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10410","display_name":"COVID-19 epidemiological studies","score":0.9883999824523926,"subfield":{"id":"https://openalex.org/subfields/2611","display_name":"Modeling and Simulation"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6514475345611572},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4835645854473114},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4785243272781372},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.44849681854248047},{"id":"https://openalex.org/keywords/psychological-resilience","display_name":"Psychological resilience","score":0.4275965094566345},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4257124960422516},{"id":"https://openalex.org/keywords/resilience","display_name":"Resilience (materials science)","score":0.42013463377952576},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.350789874792099},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.2205968201160431},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13924896717071533}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6514475345611572},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4835645854473114},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4785243272781372},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.44849681854248047},{"id":"https://openalex.org/C137176749","wikidata":"https://www.wikidata.org/wiki/Q4105337","display_name":"Psychological resilience","level":2,"score":0.4275965094566345},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4257124960422516},{"id":"https://openalex.org/C2779585090","wikidata":"https://www.wikidata.org/wiki/Q3457762","display_name":"Resilience (materials science)","level":2,"score":0.42013463377952576},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.350789874792099},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.2205968201160431},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13924896717071533},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3397536.3422261","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3397536.3422261","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.5,"id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G3429971190","display_name":null,"funder_award_id":"IIS-1942680, CNS-1952085, CMMI-1831140, DGE-2021871","funder_id":"https://openalex.org/F4320309085","funder_display_name":"Center for Selective C-H Functionalization, National Science Foundation"},{"id":"https://openalex.org/G8385489419","display_name":null,"funder_award_id":"69A3551747131","funder_id":"https://openalex.org/F4320306108","funder_display_name":"U.S. Department of Transportation"}],"funders":[{"id":"https://openalex.org/F4320306108","display_name":"U.S. Department of Transportation","ror":"https://ror.org/02xfw2e90"},{"id":"https://openalex.org/F4320309085","display_name":"Center for Selective C-H Functionalization, National Science Foundation","ror":"https://ror.org/02h8v7m77"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1550669880","https://openalex.org/W2002151188","https://openalex.org/W2042659752","https://openalex.org/W2099471712","https://openalex.org/W2123838014","https://openalex.org/W2528639018","https://openalex.org/W2614121823","https://openalex.org/W2734256217","https://openalex.org/W2739060064","https://openalex.org/W2755226765","https://openalex.org/W2755772211","https://openalex.org/W2808862972","https://openalex.org/W2809128166","https://openalex.org/W2900880306","https://openalex.org/W2904120175","https://openalex.org/W2904832339","https://openalex.org/W2907893404","https://openalex.org/W2910999553","https://openalex.org/W2948696683","https://openalex.org/W2963037989","https://openalex.org/W2963124587","https://openalex.org/W2967908858","https://openalex.org/W2988110904","https://openalex.org/W3003426638","https://openalex.org/W3003540860","https://openalex.org/W3005722800","https://openalex.org/W3008294222","https://openalex.org/W3010131837","https://openalex.org/W3013594674","https://openalex.org/W3014084098","https://openalex.org/W3014743679","https://openalex.org/W3033835845","https://openalex.org/W3088139267","https://openalex.org/W3088992249","https://openalex.org/W3104020727","https://openalex.org/W3105363582","https://openalex.org/W3203434175","https://openalex.org/W4300906944"],"related_works":["https://openalex.org/W2140798747","https://openalex.org/W2948169060","https://openalex.org/W2730112582","https://openalex.org/W2284759612","https://openalex.org/W2110696645","https://openalex.org/W4402320089","https://openalex.org/W2358580169","https://openalex.org/W2111347279","https://openalex.org/W4399426197","https://openalex.org/W2807251790"],"abstract_inverted_index":{"The":[0],"COVID-19":[1,80,118],"pandemic":[2],"has":[3],"posed":[4],"grand":[5],"challenges":[6],"to":[7,67,70,105,140],"policy":[8,121],"makers,":[9],"raising":[10],"major":[11],"social":[12,72],"conflicts":[13],"between":[14],"public":[15],"health":[16],"and":[17,74,96,156,169],"economic":[18],"resilience.":[19],"Policies":[20],"such":[21],"as":[22,90],"closure":[23],"or":[24],"reopen":[25],"of":[26,34,55,138,144],"businesses":[27],"are":[28],"made":[29],"based":[30,174],"on":[31],"scientific":[32],"projections":[33],"infection":[35,39,46],"risks":[36],"obtained":[37],"from":[38,124,152],"dynamics":[40,47],"models.":[41],"While":[42],"most":[43],"parameters":[44],"in":[45,110,135],"models":[48],"can":[49,162,176],"be":[50],"set":[51],"using":[52,147],"domain":[53],"knowledge":[54],"COVID-19,":[56],"a":[57,91,99,131],"key":[58],"parameter":[59],"-":[60,63],"human":[61,166],"mobility":[62,107,149,167],"is":[64],"often":[65],"challenging":[66],"estimate":[68,106],"due":[69],"complex":[71],"contexts":[73],"limited":[75],"training":[76],"data":[77,93,126,150,158],"under":[78,113],"escalating":[79],"conditions.":[81],"To":[82],"address":[83],"these":[84],"challenges,":[85],"we":[86],"formulate":[87],"the":[88,136,142,171],"problem":[89,95],"spatio-temporal":[92,100],"generation":[94],"propose":[97],"COVID-GAN,":[98],"Conditional":[101],"Generative":[102],"Adversarial":[103],"Network,":[104],"(e.g.,":[108,117],"changes":[109],"POI":[111],"visits)":[112],"various":[114],"real-world":[115,165],"conditions":[116],"severity,":[119],"local":[120],"interventions)":[122],"integrated":[123],"multiple":[125],"sources.":[127],"We":[128],"also":[129],"introduce":[130],"domain-constraint":[132,173],"correction":[133,175],"layer":[134],"generator":[137],"COVID-GAN":[139,161],"reduce":[141],"difficulty":[143],"learning.":[145],"Experiments":[146],"urban":[148],"derived":[151],"cell":[153],"phone":[154],"records":[155],"census":[157],"show":[159],"that":[160,170],"well":[163],"approximate":[164],"responses,":[168],"proposed":[172],"greatly":[177],"improve":[178],"solution":[179],"quality.":[180]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":1}],"updated_date":"2026-08-08T01:25:22.217667","created_date":"2020-12-07T00:00:00"}
