{"id":"https://openalex.org/W4403487680","doi":"https://doi.org/10.3233/faia240683","title":"Error-Driven Uncertainty Aware Training","display_name":"Error-Driven Uncertainty Aware Training","publication_year":2024,"publication_date":"2024-10-16","ids":{"openalex":"https://openalex.org/W4403487680","doi":"https://doi.org/10.3233/faia240683"},"language":"en","primary_location":{"id":"doi:10.3233/faia240683","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia240683","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA240683","source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA240683","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5107635222","display_name":"Pedro Mendes","orcid":"https://orcid.org/0000-0001-9311-6755"},"institutions":[{"id":"https://openalex.org/I121345201","display_name":"Instituto de Engenharia de Sistemas e Computadores Investiga\u00e7\u00e3o e Desenvolvimento","ror":"https://ror.org/04mqy3p58","country_code":"PT","type":"nonprofit","lineage":["https://openalex.org/I121345201","https://openalex.org/I4210125590"]},{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["PT","US"],"is_corresponding":true,"raw_author_name":"Pedro Mendes","raw_affiliation_strings":["INESC-ID and Instituto Superior Tecnico, Universidade de Lisboa","Software and Societal Systems Department, Carnegie Mellon University"],"affiliations":[{"raw_affiliation_string":"INESC-ID and Instituto Superior Tecnico, Universidade de Lisboa","institution_ids":["https://openalex.org/I121345201"]},{"raw_affiliation_string":"Software and Societal Systems Department, Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049600349","display_name":"Paolo Romano","orcid":"https://orcid.org/0000-0001-7026-7446"},"institutions":[{"id":"https://openalex.org/I121345201","display_name":"Instituto de Engenharia de Sistemas e Computadores Investiga\u00e7\u00e3o e Desenvolvimento","ror":"https://ror.org/04mqy3p58","country_code":"PT","type":"nonprofit","lineage":["https://openalex.org/I121345201","https://openalex.org/I4210125590"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Paolo Romano","raw_affiliation_strings":["INESC-ID and Instituto Superior Tecnico, Universidade de Lisboa"],"affiliations":[{"raw_affiliation_string":"INESC-ID and Instituto Superior Tecnico, Universidade de Lisboa","institution_ids":["https://openalex.org/I121345201"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045020317","display_name":"David Garlan","orcid":"https://orcid.org/0000-0002-6735-8301"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David Garlan","raw_affiliation_strings":["Software and Societal Systems Department, Carnegie Mellon University"],"affiliations":[{"raw_affiliation_string":"Software and Societal Systems Department, Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5107635222"],"corresponding_institution_ids":["https://openalex.org/I121345201","https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":5.4442,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.9627777,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9401999711990356,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9401999711990356,"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/T10906","display_name":"AI-based Problem Solving and Planning","score":0.9369000196456909,"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/training","display_name":"Training (meteorology)","score":0.7174066305160522},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5582209229469299},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38704872131347656},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1466875970363617},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.08830156922340393}],"concepts":[{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.7174066305160522},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5582209229469299},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38704872131347656},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1466875970363617},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.08830156922340393}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/faia240683","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia240683","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA240683","source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"}],"best_oa_location":{"id":"doi:10.3233/faia240683","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia240683","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA240683","source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4403487680.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W230091440","https://openalex.org/W2390279801","https://openalex.org/W2233261550","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2810751659"],"abstract_inverted_index":{"Neural":[0],"networks":[1],"are":[2,81],"often":[3],"overconfident":[4],"about":[5],"their":[6,10,39,56],"predictions,":[7],"which":[8,28],"undermines":[9],"reliability":[11],"and":[12,52,105,125,135,156,196],"trustworthiness.":[13],"In":[14],"this":[15],"work,":[16],"we":[17],"present":[18],"a":[19],"novel":[20],"technique,":[21],"named":[22],"Error-Driven":[23],"Uncertainty":[24],"Aware":[25],"Training":[26],"(EUAT),":[27],"aims":[29],"to":[30,37,43,181],"enhance":[31],"the":[32,65,78,87,93,114,128,188],"ability":[33],"of":[34,96],"neural":[35,123],"classifiers":[36,184],"estimate":[38],"uncertainty":[40,100,108,147,160],"correctly,":[41],"namely":[42],"be":[44,192],"highly":[45],"uncertain":[46,54],"when":[47,55,168,179],"they":[48],"output":[49,57,190],"inaccurate":[50],"predictions":[51],"low":[53],"is":[58],"accurate.":[59],"The":[60,138],"EUAT":[61,120,142],"approach":[62],"operates":[63],"during":[64],"model\u2019s":[66,115,189],"training":[67,79,152],"phase":[68],"by":[69,86,158],"selectively":[70],"employing":[71],"two":[72],"loss":[73],"functions":[74],"depending":[75],"on":[76],"whether":[77,187],"examples":[80],"correctly":[82,102],"or":[83,194],"incorrectly":[84],"predicted":[85,103],"model.":[88],"This":[89],"allows":[90],"for":[91,101,109,146],"pursuing":[92],"twofold":[94],"goal":[95],"i)":[97],"minimizing":[98],"model":[99],"inputs":[104],"ii)":[106],"maximizing":[107],"mispredicted":[110],"inputs,":[111],"while":[112],"preserving":[113],"misprediction":[116],"rate.":[117],"We":[118],"evaluate":[119],"using":[121],"diverse":[122],"models":[124],"datasets":[126],"in":[127],"image":[129],"recognition":[130],"domains":[131],"considering":[132],"both":[133],"non-adversarial":[134],"adversarial":[136],"settings.":[137],"results":[139],"show":[140],"that":[141,162,185],"outperforms":[143],"existing":[144],"approaches":[145],"estimation":[148],"(including":[149],"other":[150],"uncertainty-aware":[151],"techniques,":[153],"calibration,":[154],"ensembles,":[155],"DEUP)":[157],"providing":[159],"estimates":[161],"not":[163,195],"only":[164],"have":[165],"higher":[166],"quality":[167],"evaluated":[169],"via":[170],"statistical":[171],"metrics":[172],"(e.g.,":[173],"correlation":[174],"with":[175],"residuals)":[176],"but":[177],"also":[178],"employed":[180],"build":[182],"binary":[183],"decide":[186],"can":[191],"trusted":[193],"under":[197],"distributional":[198],"data":[199],"shifts.":[200]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}