{"id":"https://openalex.org/W4400413710","doi":"https://doi.org/10.1080/10618600.2024.2374962","title":"Fast Computer Model Calibration using Annealed and Transformed Variational Inference","display_name":"Fast Computer Model Calibration using Annealed and Transformed Variational Inference","publication_year":2024,"publication_date":"2024-07-08","ids":{"openalex":"https://openalex.org/W4400413710","doi":"https://doi.org/10.1080/10618600.2024.2374962"},"language":"en","primary_location":{"id":"doi:10.1080/10618600.2024.2374962","is_oa":false,"landing_page_url":"https://doi.org/10.1080/10618600.2024.2374962","pdf_url":null,"source":{"id":"https://openalex.org/S76159266","display_name":"Journal of Computational and Graphical Statistics","issn_l":"1061-8600","issn":["1061-8600","1537-2715"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational and Graphical Statistics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://figshare.com/articles/journal_contribution/Fast_Computer_Model_Calibration_using_Annealed_and_Transformed_Variational_Inference/26207480","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5070031291","display_name":"Dongkyu Cho","orcid":null},"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"]},{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR","US"],"is_corresponding":false,"raw_author_name":"Dongkyu Derek Cho","raw_affiliation_strings":["Department of Statistical Science, Duke University","Department of Statistics and Data Science, Yonsei University","Department of Statistical Science, Duke University, Durham, NC","Department of Statistics and Data Science, Yonsei University, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistical Science, Duke University","institution_ids":["https://openalex.org/I170897317"]},{"raw_affiliation_string":"Department of Statistics and Data Science, Yonsei University","institution_ids":["https://openalex.org/I193775966"]},{"raw_affiliation_string":"Department of Statistical Science, Duke University, Durham, NC","institution_ids":["https://openalex.org/I170897317"]},{"raw_affiliation_string":"Department of Statistics and Data Science, Yonsei University, Seoul, South Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010464799","display_name":"Won Chang","orcid":"https://orcid.org/0000-0003-3556-1249"},"institutions":[{"id":"https://openalex.org/I63135867","display_name":"University of Cincinnati","ror":"https://ror.org/01e3m7079","country_code":"US","type":"education","lineage":["https://openalex.org/I63135867"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Won Chang","raw_affiliation_strings":["Division of Statistics and Data Science, University of Cincinnati","Division of Statistics and Data Science, University of Cincinnati, Cincinnati, OH"],"raw_orcid":"https://orcid.org/0000-0003-3556-1249","affiliations":[{"raw_affiliation_string":"Division of Statistics and Data Science, University of Cincinnati","institution_ids":["https://openalex.org/I63135867"]},{"raw_affiliation_string":"Division of Statistics and Data Science, University of Cincinnati, Cincinnati, OH","institution_ids":["https://openalex.org/I63135867"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100359863","display_name":"Jaewoo Park","orcid":"https://orcid.org/0000-0002-7900-5749"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jaewoo Park","raw_affiliation_strings":["Department of Applied Statistics, Yonsei University","Department of Statistics and Data Science, Yonsei University","Department of Statistics and Data Science, Yonsei University, Seoul, South Korea","Department of Applied Statistics, Yonsei University, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Applied Statistics, Yonsei University","institution_ids":["https://openalex.org/I193775966"]},{"raw_affiliation_string":"Department of Statistics and Data Science, Yonsei University","institution_ids":["https://openalex.org/I193775966"]},{"raw_affiliation_string":"Department of Statistics and Data Science, Yonsei University, Seoul, South Korea","institution_ids":["https://openalex.org/I193775966"]},{"raw_affiliation_string":"Department of Applied Statistics, Yonsei University, Seoul, South Korea","institution_ids":["https://openalex.org/I193775966"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5010464799"],"corresponding_institution_ids":["https://openalex.org/I63135867"],"apc_list":null,"apc_paid":null,"fwci":0.2482,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.50913201,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"34","issue":"2","first_page":"474","last_page":"487"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11236","display_name":"Control Systems and Identification","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10597","display_name":"Nuclear reactor physics and engineering","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.649285078048706},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.6431877017021179},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5088624954223633},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.49422934651374817},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4048275053501129},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.40045076608657837},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3545301854610443},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.25565803050994873}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.649285078048706},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.6431877017021179},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5088624954223633},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49422934651374817},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4048275053501129},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.40045076608657837},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3545301854610443},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.25565803050994873}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1080/10618600.2024.2374962","is_oa":false,"landing_page_url":"https://doi.org/10.1080/10618600.2024.2374962","pdf_url":null,"source":{"id":"https://openalex.org/S76159266","display_name":"Journal of Computational and Graphical Statistics","issn_l":"1061-8600","issn":["1061-8600","1537-2715"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational and Graphical Statistics","raw_type":"journal-article"},{"id":"pmh:oai:figshare.com:article/26207480","is_oa":true,"landing_page_url":null,"pdf_url":"https://figshare.com/articles/journal_contribution/Fast_Computer_Model_Calibration_using_Annealed_and_Transformed_Variational_Inference/26207480","source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},{"id":"doi:10.6084/m9.figshare.26207480.v1","is_oa":true,"landing_page_url":"https://doi.org/10.6084/m9.figshare.26207480.v1","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"pmh:oai:figshare.com:article/26207480","is_oa":true,"landing_page_url":null,"pdf_url":"https://figshare.com/articles/journal_contribution/Fast_Computer_Model_Calibration_using_Annealed_and_Transformed_Variational_Inference/26207480","source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2017571606","display_name":null,"funder_award_id":"2020R1C1C1A0100386814","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G7514333950","display_name":null,"funder_award_id":"RS-2023-00217705","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4400413710.pdf","grobid_xml":"https://content.openalex.org/works/W4400413710.grobid-xml"},"referenced_works_count":54,"referenced_works":["https://openalex.org/W366402269","https://openalex.org/W1513873506","https://openalex.org/W1534417711","https://openalex.org/W1571863136","https://openalex.org/W1973333099","https://openalex.org/W1984448240","https://openalex.org/W2003884505","https://openalex.org/W2006763045","https://openalex.org/W2018044188","https://openalex.org/W2025909913","https://openalex.org/W2053357201","https://openalex.org/W2078454401","https://openalex.org/W2116416291","https://openalex.org/W2139812092","https://openalex.org/W2163669663","https://openalex.org/W2225156818","https://openalex.org/W2279857902","https://openalex.org/W2290226688","https://openalex.org/W2309645253","https://openalex.org/W2356183642","https://openalex.org/W2497151737","https://openalex.org/W2543468432","https://openalex.org/W2587284713","https://openalex.org/W2612574351","https://openalex.org/W2765076328","https://openalex.org/W2772124661","https://openalex.org/W2791004381","https://openalex.org/W2798709976","https://openalex.org/W2806359692","https://openalex.org/W2902424187","https://openalex.org/W2909941368","https://openalex.org/W2924835211","https://openalex.org/W2959716150","https://openalex.org/W2962851448","https://openalex.org/W2962994101","https://openalex.org/W2963045461","https://openalex.org/W2963839891","https://openalex.org/W2992005611","https://openalex.org/W2992035660","https://openalex.org/W3011674709","https://openalex.org/W3038411645","https://openalex.org/W3081827255","https://openalex.org/W3098780406","https://openalex.org/W3150807214","https://openalex.org/W3173491913","https://openalex.org/W3204937802","https://openalex.org/W3205748757","https://openalex.org/W4280648529","https://openalex.org/W6610566761","https://openalex.org/W6682044371","https://openalex.org/W6712471759","https://openalex.org/W6728823957","https://openalex.org/W6763486065","https://openalex.org/W6780546012"],"related_works":["https://openalex.org/W2051487156","https://openalex.org/W2073681303","https://openalex.org/W2053286651","https://openalex.org/W2055243143","https://openalex.org/W2181743346","https://openalex.org/W2187401768","https://openalex.org/W2181413294","https://openalex.org/W2989452537","https://openalex.org/W2052122378","https://openalex.org/W2544423928"],"abstract_inverted_index":{"Computer":[0],"models":[1,29,103,171],"play":[2],"a":[3,71,116,156,173],"crucial":[4],"role":[5],"in":[6,119,152],"numerous":[7],"scientific":[8],"and":[9,61,86,146,161,172,184],"engineering":[10],"domains.":[11],"To":[12,90],"ensure":[13],"the":[14,24,37,55,111,127,136,139,178],"accuracy":[15],"of":[16,27,58,138,158],"simulations,":[17],"it":[18],"is":[19,36],"essential":[20],"to":[21,54,74,83,122,168,188],"properly":[22],"calibrate":[23],"input":[25],"parameters":[26],"these":[28,92],"through":[30,155],"statistical":[31],"inference.":[32],"While":[33],"Bayesian":[34,76],"inference":[35,67,186],"standard":[38],"approach":[39],"for":[40],"this":[41],"task,":[42],"employing":[43],"Markov":[44],"Chain":[45],"Monte":[46],"Carlo":[47],"methods":[48,98],"often":[49],"encounters":[50],"computational":[51],"hurdles":[52],"due":[53,82],"costly":[56],"evaluation":[57],"likelihood":[59],"functions":[60],"slow":[62],"mixing":[63],"rates.":[64],"Although":[65],"variational":[66,112],"(VI)":[68],"can":[69,148,181],"be":[70],"fast":[72,183],"alternative":[73],"traditional":[75],"approaches,":[77],"VI":[78,97],"has":[79],"limited":[80],"applicability":[81],"boundary":[84],"issues":[85],"local":[87,153],"optima":[88,154],"problems.":[89],"address":[91],"challenges,":[93],"we":[94,130],"propose":[95],"flexible":[96],"based":[99],"on":[100,110],"deep":[101],"generative":[102],"that":[104,134,177],"do":[105],"not":[106],"require":[107],"parametric":[108],"assumptions":[109],"distribution.":[113],"We":[114,164],"embed":[115],"surjective":[117],"transformation":[118],"our":[120,142,166],"framework":[121],"avoid":[123],"posterior":[124],"truncation":[125],"at":[126],"boundary.":[128],"Additionally,":[129],"provide":[131,182],"theoretical":[132],"conditions":[133],"guarantee":[135],"success":[137],"algorithm.":[140],"Furthermore,":[141],"temperature":[143],"annealing":[144],"scheme":[145],"fine-tuning":[147],"prevent":[149],"being":[150],"trapped":[151],"series":[157],"intermediate":[159],"posteriors":[160],"weight":[162],"adjustment.":[163],"apply":[165],"method":[167,180],"infectious":[169],"disease":[170],"geophysical":[174],"model,":[175],"illustrating":[176],"proposed":[179],"accurate":[185],"compared":[187],"its":[189],"competitors.":[190]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-15T08:34:33.830935","created_date":"2025-10-10T00:00:00"}