{"id":"https://openalex.org/W4391786690","doi":"https://doi.org/10.1145/3648005","title":"Out-of-distribution Detection in Dependent Data for Cyber-physical Systems with Conformal Guarantees","display_name":"Out-of-distribution Detection in Dependent Data for Cyber-physical Systems with Conformal Guarantees","publication_year":2024,"publication_date":"2024-02-13","ids":{"openalex":"https://openalex.org/W4391786690","doi":"https://doi.org/10.1145/3648005"},"language":"en","primary_location":{"id":"doi:10.1145/3648005","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3648005","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3648005","source":{"id":"https://openalex.org/S2506189754","display_name":"ACM Transactions on Cyber-Physical Systems","issn_l":"2378-962X","issn":["2378-962X","2378-9638"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Cyber-Physical Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3648005","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5087919330","display_name":"Ramneet Kaur","orcid":"https://orcid.org/0009-0007-7662-3174"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]},{"id":"https://openalex.org/I922845939","display_name":"Philadelphia University","ror":"https://ror.org/03zzmyz63","country_code":"US","type":"education","lineage":["https://openalex.org/I922845939"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ramneet Kaur","raw_affiliation_strings":["University of Pennsylvania, Philadelphia, USA"],"raw_orcid":"https://orcid.org/0009-0007-7662-3174","affiliations":[{"raw_affiliation_string":"University of Pennsylvania, Philadelphia, USA","institution_ids":["https://openalex.org/I79576946","https://openalex.org/I922845939"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101572701","display_name":"Yahan Yang","orcid":"https://orcid.org/0000-0003-3233-1720"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]},{"id":"https://openalex.org/I922845939","display_name":"Philadelphia University","ror":"https://ror.org/03zzmyz63","country_code":"US","type":"education","lineage":["https://openalex.org/I922845939"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yahan Yang","raw_affiliation_strings":["University of Pennsylvania, Philadelphia, USA"],"raw_orcid":"https://orcid.org/0000-0003-3233-1720","affiliations":[{"raw_affiliation_string":"University of Pennsylvania, Philadelphia, USA","institution_ids":["https://openalex.org/I79576946","https://openalex.org/I922845939"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082105260","display_name":"Oleg Sokolsky","orcid":"https://orcid.org/0000-0001-5282-0658"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]},{"id":"https://openalex.org/I922845939","display_name":"Philadelphia University","ror":"https://ror.org/03zzmyz63","country_code":"US","type":"education","lineage":["https://openalex.org/I922845939"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Oleg Sokolsky","raw_affiliation_strings":["University of Pennsylvania, Philadelphia, USA"],"raw_orcid":"https://orcid.org/0000-0001-5282-0658","affiliations":[{"raw_affiliation_string":"University of Pennsylvania, Philadelphia, USA","institution_ids":["https://openalex.org/I79576946","https://openalex.org/I922845939"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030456600","display_name":"Insup Lee","orcid":"https://orcid.org/0000-0003-2672-1132"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Insup Lee","raw_affiliation_strings":["Department of Computer and Information, University of Pennsylvania, Philadelphia, USA"],"raw_orcid":"https://orcid.org/0000-0003-2672-1132","affiliations":[{"raw_affiliation_string":"Department of Computer and Information, University of Pennsylvania, Philadelphia, USA","institution_ids":["https://openalex.org/I79576946"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9737,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.77838726,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"8","issue":"4","first_page":"1","last_page":"27"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998000264167786,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9958999752998352,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9684000015258789,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/computer-science","display_name":"Computer science","score":0.6181127429008484},{"id":"https://openalex.org/keywords/sliding-window-protocol","display_name":"Sliding window protocol","score":0.5659060478210449},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5517223477363586},{"id":"https://openalex.org/keywords/trace","display_name":"TRACE (psycholinguistics)","score":0.5467017292976379},{"id":"https://openalex.org/keywords/bounded-function","display_name":"Bounded function","score":0.5121979117393494},{"id":"https://openalex.org/keywords/conformal-map","display_name":"Conformal map","score":0.5048907399177551},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.47034600377082825},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4468650221824646},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.4354023337364197},{"id":"https://openalex.org/keywords/false-alarm","display_name":"False alarm","score":0.41015005111694336},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4004803001880646},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37906700372695923},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3469699025154114},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2719596028327942},{"id":"https://openalex.org/keywords/window","display_name":"Window (computing)","score":0.10957193374633789}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6181127429008484},{"id":"https://openalex.org/C102392041","wikidata":"https://www.wikidata.org/wiki/Q592860","display_name":"Sliding window protocol","level":3,"score":0.5659060478210449},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5517223477363586},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.5467017292976379},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.5121979117393494},{"id":"https://openalex.org/C98214594","wikidata":"https://www.wikidata.org/wiki/Q850275","display_name":"Conformal map","level":2,"score":0.5048907399177551},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.47034600377082825},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4468650221824646},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.4354023337364197},{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.41015005111694336},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4004803001880646},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37906700372695923},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3469699025154114},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2719596028327942},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.10957193374633789},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3648005","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3648005","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3648005","source":{"id":"https://openalex.org/S2506189754","display_name":"ACM Transactions on Cyber-Physical Systems","issn_l":"2378-962X","issn":["2378-962X","2378-9638"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Cyber-Physical Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1145/3648005","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3648005","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3648005","source":{"id":"https://openalex.org/S2506189754","display_name":"ACM Transactions on Cyber-Physical Systems","issn_l":"2378-962X","issn":["2378-962X","2378-9638"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Cyber-Physical Systems","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.4099999964237213,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4391786690.pdf","grobid_xml":"https://content.openalex.org/works/W4391786690.grobid-xml"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W874179280","https://openalex.org/W1975868529","https://openalex.org/W1978666674","https://openalex.org/W1985889176","https://openalex.org/W2008958337","https://openalex.org/W2067713319","https://openalex.org/W2112796928","https://openalex.org/W2138906212","https://openalex.org/W2599743206","https://openalex.org/W2886281300","https://openalex.org/W2963155035","https://openalex.org/W2990789488","https://openalex.org/W3007103823","https://openalex.org/W3019826645","https://openalex.org/W3023215041","https://openalex.org/W3027099759","https://openalex.org/W3035249419","https://openalex.org/W3043138801","https://openalex.org/W3080932444","https://openalex.org/W3128229642","https://openalex.org/W3149938609","https://openalex.org/W3185507903","https://openalex.org/W3195288334","https://openalex.org/W3195576835","https://openalex.org/W3200940659","https://openalex.org/W3210733870","https://openalex.org/W3214507387","https://openalex.org/W4281492437","https://openalex.org/W4282984117","https://openalex.org/W4283394624","https://openalex.org/W4283796600","https://openalex.org/W4307022340","https://openalex.org/W4321648929","https://openalex.org/W4367047199","https://openalex.org/W4367398852","https://openalex.org/W4368362764","https://openalex.org/W4385730888","https://openalex.org/W6776937213","https://openalex.org/W6800618455"],"related_works":["https://openalex.org/W2353818951","https://openalex.org/W1605879311","https://openalex.org/W2061122711","https://openalex.org/W2611980620","https://openalex.org/W4247954915","https://openalex.org/W2131958170","https://openalex.org/W1971223889","https://openalex.org/W2385763735","https://openalex.org/W2273754158","https://openalex.org/W205872183"],"abstract_inverted_index":{"Uncertainty":[0],"in":[1,10,31,52,67,78,102,110,195,233,266,379],"the":[2,18,32,79,94,99,124,136,160,192,196,230,234,238,248,258,316,328,333,352,359,363,369,380],"predictions":[3,117,130],"of":[4,21,29,36,151,159,173,191,229,260,362],"learning-enabled":[5,23],"components":[6],"hinders":[7],"their":[8],"deployment":[9],"safety-critical":[11],"cyber-physical":[12],"systems":[13],"(CPS).":[14],"A":[15],"shift":[16,38],"from":[17,93,118],"training":[19],"distribution":[20],"a":[22,59,204,296],"component":[24],"(LEC)":[25],"is":[26,279,294,309],"one":[27,278],"source":[28],"uncertainty":[30],"LEC\u2019s":[33],"predictions.":[34],"Detection":[35],"this":[37],"or":[39,81,302],"out-of-distribution":[40],"(OOD)":[41],"detection":[42,66,105,109,147,168,246,272,321],"on":[43,87,123,148,169,247,273,280,295,322,332,351,358],"individual":[44],"datapoints":[45,154],"has":[46],"therefore":[47],"gained":[48],"attention":[49],"recently.":[50],"But":[51],"many":[53],"applications,":[54],"inputs":[55],"to":[56,135,187,225,315],"CPS":[57,71,298,339],"form":[58],"temporal":[60,76,96],"sequence.":[61],"Existing":[62],"techniques":[63],"for":[64,70,107,113,244,270,299,340],"OOD":[65,108,146,167,245,271,320],"time-series":[68,111,153,171],"data":[69,112,308],"either":[72],"do":[73,82],"not":[74,83],"exploit":[75],"relationships":[77],"sequence":[80],"provide":[84],"any":[85],"guarantees":[86,373],"detection.":[88],"We":[89,163,256,343,366],"propose":[90,165],"using":[91,156,185],"deviation":[92],"in-distribution":[95],"equivariance":[97],"as":[98,210],"non-conformity":[100],"measure":[101,126],"conformal":[103,120],"anomaly":[104],"framework":[106],"CPS.":[114],"Computing":[115],"independent":[116],"multiple":[119],"detectors":[121],"based":[122],"proposed":[125,137],"and":[127,199,219,237,337,388],"combining":[128,200],"these":[129,201,375],"by":[131,155,184,203,262,356,374],"Fisher\u2019s":[132],"method":[133],"leads":[134],"detector":[138],"CODiT":[139,144,186,261,357],"with":[140,176,250,285,311,347],"bounded":[141,177,251],"false":[142,178,252,370],"alarms.":[143,179],"performs":[145],"fixed-length":[149,274],"windows":[150,194,232,361],"consecutive":[152],"Fisher":[157,189,227,353],"value":[158,240],"input":[161,197,235,364],"window.":[162],"further":[164],"performing":[166],"real-time":[170],"traces":[172],"variable":[174,323],"lengths":[175],"This":[180],"can":[181,222,241],"be":[182,223,242],"done":[183],"compute":[188],"values":[190,202,228,354],"sliding":[193,231,360],"trace":[198,249],"merging":[205,349,377],"function.":[206],"Merging":[207],"functions":[208,350,378],"such":[209],"Harmonic":[211],"Mean,":[212,214,216],"Arithmetic":[213],"Geometric":[215],"Bonferroni":[217],"Method,":[218],"so":[220],"on,":[221],"used":[224,243],"combine":[226],"trace,":[236],"combined":[239],"alarm":[253,371],"rate":[254,372],"guarantees.":[255],"illustrate":[257],"efficacy":[259],"achieving":[263],"state-of-the-art":[264],"results":[265,346],"two":[267],"case":[268,292,330,384],"studies":[269,331],"windows.":[275],"The":[276,290],"first":[277],"an":[281],"autonomous":[282,334,381],"driving":[283,335,382],"system":[284,336,383],"perception":[286],"(or":[287],"vision)":[288],"LEC.":[289],"second":[291],"study":[293],"medical":[297,338],"walking":[300],"pattern":[301],"GAIT":[303,341],"analysis":[304],"where":[305],"physiological":[306],"(non-vision)":[307],"collected":[310],"force-sensitive":[312],"resistors":[313],"attached":[314],"subject\u2019s":[317],"body.":[318],"For":[319],"length":[324],"traces,":[325],"we":[326],"consider":[327],"same":[329],"analysis.":[342],"report":[344],"our":[345],"four":[348,376],"computed":[355],"trace.":[365],"also":[367],"compare":[368],"study.":[385],"Code,":[386],"data,":[387],"trained":[389],"models":[390],"are":[391],"available":[392],"at":[393],"https://github.com/kaustubhsridhar/time-series-OOD":[394],".":[395]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
