{"id":"https://openalex.org/W7160620703","doi":"https://doi.org/10.48550/arxiv.2605.06612","title":"Online Bayesian Calibration under Gradual and Abrupt System Changes","display_name":"Online Bayesian Calibration under Gradual and Abrupt System Changes","publication_year":2026,"publication_date":"2026-05-07","ids":{"openalex":"https://openalex.org/W7160620703","doi":"https://doi.org/10.48550/arxiv.2605.06612"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.06612","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.06612","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.06612","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135679813","display_name":"Yang Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Yang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5035632114","display_name":"Chiwoo Park","orcid":"https://orcid.org/0000-0002-2463-8901"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Park, Chiwoo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10791","display_name":"Advanced Control Systems Optimization","score":0.23240000009536743,"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"}},"topics":[{"id":"https://openalex.org/T10791","display_name":"Advanced Control Systems Optimization","score":0.23240000009536743,"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/T11206","display_name":"Model Reduction and Neural Networks","score":0.12950000166893005,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.12219999730587006,"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/calibration","display_name":"Calibration","score":0.7324000000953674},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.6129999756813049},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5702999830245972},{"id":"https://openalex.org/keywords/spurious-relationship","display_name":"Spurious relationship","score":0.4578999876976013},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.4465000033378601},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.41760000586509705},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.3919999897480011},{"id":"https://openalex.org/keywords/data-assimilation","display_name":"Data assimilation","score":0.3790000081062317}],"concepts":[{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.7324000000953674},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6287999749183655},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.6129999756813049},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5702999830245972},{"id":"https://openalex.org/C97256817","wikidata":"https://www.wikidata.org/wiki/Q1462316","display_name":"Spurious relationship","level":2,"score":0.4578999876976013},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.4465000033378601},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.41760000586509705},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.3919999897480011},{"id":"https://openalex.org/C24552861","wikidata":"https://www.wikidata.org/wiki/Q2670177","display_name":"Data assimilation","level":2,"score":0.3790000081062317},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37470000982284546},{"id":"https://openalex.org/C122770356","wikidata":"https://www.wikidata.org/wiki/Q1656753","display_name":"Identifiability","level":2,"score":0.36340001225471497},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.32899999618530273},{"id":"https://openalex.org/C2777851325","wikidata":"https://www.wikidata.org/wiki/Q7094102","display_name":"Online model","level":2,"score":0.32199999690055847},{"id":"https://openalex.org/C11210021","wikidata":"https://www.wikidata.org/wiki/Q1520713","display_name":"Linearization","level":3,"score":0.30970001220703125},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.28369998931884766},{"id":"https://openalex.org/C2778049539","wikidata":"https://www.wikidata.org/wiki/Q17002908","display_name":"Bayesian optimization","level":2,"score":0.27619999647140503},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2745000123977661},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.2718999981880188},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.27149999141693115},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.26739999651908875}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.06612","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.06612","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.06612","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.06612","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Bayesian":[0,29,106,113,231],"model":[1,14,26,39,94],"calibration":[2,21,30,114,127,139,176,210,232],"is":[3,47,164],"central":[4],"to":[5,38,128,229],"digital":[6,65],"twins":[7],"and":[8,23,34,46,73,78,97,122,173,191,193,203,221,233],"computer":[9],"experiments,":[10],"as":[11,50],"it":[12],"aligns":[13],"outputs":[15],"with":[16,166],"field":[17],"observations":[18],"by":[19,132],"estimating":[20],"parameters":[22,33,140],"correcting":[24],"systematic":[25,95],"bias.":[27],"Classical":[28],"introduces":[31],"latent":[32],"a":[35,55,134,142],"discrepancy":[36],"function":[37],"bias,":[40],"but":[41],"suffers":[42],"from":[43,141],"parameter--discrepancy":[44],"confounding":[45],"typically":[48],"formulated":[49],"an":[51,111],"offline":[52],"procedure":[53],"under":[54,101,119,155,188,212,224],"stationary":[56],"data-generating":[57],"assumption.":[58],"These":[59],"limitations":[60],"are":[61,98],"restrictive":[62],"in":[63],"modern":[64],"twin":[66],"applications,":[67],"where":[68],"systems":[69],"evolve":[70],"over":[71],"time":[72],"may":[74],"exhibit":[75],"gradual":[76,156,189,213],"drift":[77],"abrupt":[79,102,161,225],"regime":[80,171,226],"shifts.":[81],"While":[82],"data":[83,118,234],"assimilation":[84,235],"methods":[85],"enable":[86],"sequential":[87],"updates,":[88],"they":[89],"generally":[90],"do":[91],"not":[92],"explicitly":[93],"bias":[96],"less":[99],"effective":[100],"changes.":[103],"We":[104,178],"propose":[105],"Recursive":[107],"Projected":[108],"Calibration":[109],"(BRPC),":[110],"online":[112,130],"framework":[115],"for":[116,138,147,182,196],"streaming":[117],"simulator":[120],"mismatch":[121],"nonstationarity.":[123],"BRPC":[124,163,208,217],"extends":[125],"projected":[126],"the":[129,175],"setting":[131],"separating":[133],"discrepancy-free":[135],"particle":[136],"update":[137,146],"conditional":[143],"Gaussian":[144],"process":[145],"discrepancy,":[148],"preserving":[149],"identifiability":[150],"while":[151,215],"enabling":[152],"bias-aware":[153],"adaptation":[154],"system":[157],"evolution.":[158],"To":[159],"handle":[160],"changes,":[162,214],"integrated":[165],"restart":[167,197],"mechanisms":[168],"that":[169,207],"detect":[170],"shifts":[172,227],"reset":[174],"process.":[177],"establish":[179],"theoretical":[180],"guarantees":[181],"both":[183],"components,":[184],"including":[185],"tracking":[186],"performance":[187,223],"evolution":[190],"false-alarm":[192],"detection":[194],"behavior":[195],"mechanisms.":[198],"Empirical":[199],"studies":[200],"on":[201],"synthetic":[202],"plant-simulation":[204],"benchmarks":[205],"show":[206],"improves":[209,219],"accuracy":[211],"restart-augmented":[216],"further":[218],"robustness":[220],"predictive":[222],"compared":[228],"sliding-window":[230],"baselines.":[236]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-09T00:00:00"}
