{"id":"https://openalex.org/W6948364041","doi":"https://doi.org/10.48550/arxiv.2506.19895","title":"A Framework for Uncertainty Quantification Based on Nearest Neighbors Across Layers","display_name":"A Framework for Uncertainty Quantification Based on Nearest Neighbors Across Layers","publication_year":2025,"publication_date":"2025-06-24","ids":{"openalex":"https://openalex.org/W6948364041","doi":"https://doi.org/10.48550/arxiv.2506.19895"},"language":"en","primary_location":{"id":"doi:10.48550/arxiv.2506.19895","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2506.19895","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2506.19895","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Font, Miguel N.","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Font, Miguel N.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Jorro-Aragoneses, Jos\u00e9 L.","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jorro-Aragoneses, Jos\u00e9 L.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Ala\u00edz, Carlos M.","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ala\u00edz, Carlos M.","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":true,"primary_topic":{"id":"https://openalex.org/T13919","display_name":"Medicinal plant effects and applications","score":0.09440000355243683,"subfield":{"id":"https://openalex.org/subfields/2707","display_name":"Complementary and alternative medicine"},"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/T13919","display_name":"Medicinal plant effects and applications","score":0.09440000355243683,"subfield":{"id":"https://openalex.org/subfields/2707","display_name":"Complementary and alternative medicine"},"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/T13568","display_name":"Wood and Agarwood Research","score":0.04749999940395355,"subfield":{"id":"https://openalex.org/subfields/1605","display_name":"Organic Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10895","display_name":"Species Distribution and Climate Change","score":0.030300000682473183,"subfield":{"id":"https://openalex.org/subfields/2302","display_name":"Ecological Modeling"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.588100016117096},{"id":"https://openalex.org/keywords/uncertainty-quantification","display_name":"Uncertainty quantification","score":0.4966999888420105},{"id":"https://openalex.org/keywords/measurement-uncertainty","display_name":"Measurement uncertainty","score":0.4625000059604645},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.45010000467300415},{"id":"https://openalex.org/keywords/decision-boundary","display_name":"Decision boundary","score":0.34880000352859497},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3409000039100647},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.3314000070095062}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6510999798774719},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.588100016117096},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5837000012397766},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5410000085830688},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.49889999628067017},{"id":"https://openalex.org/C32230216","wikidata":"https://www.wikidata.org/wiki/Q7882499","display_name":"Uncertainty quantification","level":2,"score":0.4966999888420105},{"id":"https://openalex.org/C137209882","wikidata":"https://www.wikidata.org/wiki/Q1403517","display_name":"Measurement uncertainty","level":2,"score":0.4625000059604645},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.45010000467300415},{"id":"https://openalex.org/C42023084","wikidata":"https://www.wikidata.org/wiki/Q5249231","display_name":"Decision boundary","level":3,"score":0.34880000352859497},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3409000039100647},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.3314000070095062},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.32519999146461487},{"id":"https://openalex.org/C123614077","wikidata":"https://www.wikidata.org/wiki/Q1364905","display_name":"Propagation of uncertainty","level":2,"score":0.3221000134944916},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.31119999289512634},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.2921000123023987},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.28349998593330383},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.2732999920845032},{"id":"https://openalex.org/C107327155","wikidata":"https://www.wikidata.org/wiki/Q330268","display_name":"Decision support system","level":2,"score":0.250900000333786}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2506.19895","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2506.19895","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2506.19895","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2506.19895","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.7656126618385315}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Neural":[0],"Networks":[1],"have":[2,79],"high":[3],"accuracy":[4],"in":[5,30,108,118,138],"solving":[6],"problems":[7],"where":[8],"it":[9],"is":[10,47],"difficult":[11],"to":[12,41,84],"detect":[13,42],"patterns":[14],"or":[15,36],"create":[16],"a":[17,62,71,80,119],"logical":[18],"model.":[19],"However,":[20],"these":[21,45,92,132],"algorithms":[22],"sometimes":[23],"return":[24],"wrong":[25],"solutions,":[26],"which":[27,105],"become":[28],"problematic":[29],"high-risk":[31],"domains":[32],"like":[33],"medical":[34],"diagnosis":[35],"autonomous":[37],"driving.":[38],"One":[39],"strategy":[40],"and":[43,102,126],"mitigate":[44],"errors":[46],"the":[48,51,68,85],"measurement":[49],"of":[50,70],"uncertainty":[52,69,135],"over":[53],"neural":[54],"network":[55],"decisions.":[56],"In":[57],"this":[58],"paper,":[59],"we":[60,95],"present":[61],"novel":[63],"post-hoc":[64],"framework":[65],"for":[66,87,122],"measuring":[67],"decision":[72],"based":[73],"on":[74,91],"retrieved":[75,93],"training":[76],"cases":[77],"that":[78,131],"similar":[81],"activation":[82],"vector":[83],"query":[86],"each":[88],"layer.":[89],"Based":[90],"cases,":[94],"propose":[96],"two":[97,123],"new":[98],"metrics:":[99],"Decision":[100],"Change":[101],"Layer":[103],"Uncertainty,":[104],"capture":[106],"changes":[107],"nearest-neighbor":[109],"class":[110],"distributions":[111],"across":[112],"layers.":[113],"We":[114],"evaluated":[115],"our":[116],"approach":[117],"classification":[120,140],"model":[121],"datasets:":[124],"CIFAR-10":[125],"MNIST.":[127],"The":[128],"results":[129],"show":[130],"metrics":[133],"enhance":[134],"estimation,":[136],"especially":[137],"challenging":[139],"tasks,":[141],"outperforming":[142],"softmax-based":[143],"confidence.":[144]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2025-10-10T00:00:00"}