{"id":"https://openalex.org/W7080694014","doi":null,"title":"Out-of-distribution detection in open-world machine learning: new algorithms, learning scenarios, and pathways towards safe artificial intelligence","display_name":"Out-of-distribution detection in open-world machine learning: new algorithms, learning scenarios, and pathways towards safe artificial intelligence","publication_year":2024,"publication_date":"2024-12-16","ids":{"openalex":"https://openalex.org/W7080694014"},"language":"en","primary_location":{"id":"pmh:oai:loyola.biblioteca.deusto.es:11656/28851","doi":null,"is_oa":true,"landing_page_url":"https://hdl.handle.net/20.500.14454/2398","pdf_url":"https://deustoteka.deusto.es/bitstreams/725d0674-e9ae-4d42-a09a-273945e3673e/download","source":{"id":"https://openalex.org/S4306401525","display_name":"Basque Digital Memory (Vital Foundation)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I134113660","host_organization_name":"University of Nevada, Reno","host_organization_lineage":["https://openalex.org/I134113660"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"doctoral thesis"},"volume":null,"type":"dissertation","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://deustoteka.deusto.es/bitstreams/725d0674-e9ae-4d42-a09a-273945e3673e/download","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5079795746","display_name":"Aitor Mart\u00ednez-Seras","orcid":"https://orcid.org/0000-0003-3803-3193","observed_orcids":["https://orcid.org/0000-0003-3803-3193"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Mart\u00ednez Seras, Aitor","raw_affiliation_strings":["Department of Mechanics, Design, and Industrial Organization"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mechanics, Design, and Industrial Organization","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5079795746"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.986299991607666,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.986299991607666,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.003000000026077032,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.0019000000320374966,"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/out-of-distribution-detection","display_name":"out-of-distribution detection","score":1.0},{"id":"https://openalex.org/keywords/ai-safety","display_name":"AI safety","score":0.7429999709129333},{"id":"https://openalex.org/keywords/model-robustness","display_name":"model robustness","score":0.8149999976158142},{"id":"https://openalex.org/keywords/spiking-neural-networks","display_name":"spiking neural networks","score":0.9629999995231628},{"id":"https://openalex.org/keywords/object-detection","display_name":"object detection","score":0.9860000014305115},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"reinforcement learning","score":0.9800000190734863},{"id":"https://openalex.org/keywords/knowledge-gaps","display_name":"knowledge gaps","score":0.6449999809265137},{"id":"https://openalex.org/keywords/trustworthy-ai","display_name":"trustworthy AI","score":0.45899999141693115}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6758999824523926},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6516000032424927},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6230999827384949},{"id":"https://openalex.org/C153701036","wikidata":"https://www.wikidata.org/wiki/Q659974","display_name":"Trustworthiness","level":2,"score":0.6176000237464905},{"id":"https://openalex.org/C2776900844","wikidata":"https://www.wikidata.org/wiki/Q8028383","display_name":"Witness","level":2,"score":0.4674000144004822},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.41519999504089355},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3781999945640564},{"id":"https://openalex.org/C2778012447","wikidata":"https://www.wikidata.org/wiki/Q1034415","display_name":"Scope (computer science)","level":2,"score":0.362199991941452},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.3612000048160553},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.3425000011920929},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.32120001316070557},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.266400009393692},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.2662000060081482},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.26499998569488525},{"id":"https://openalex.org/C78780964","wikidata":"https://www.wikidata.org/wiki/Q7233193","display_name":"Position paper","level":2,"score":0.25360000133514404}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:loyola.biblioteca.deusto.es:11656/28851","doi":null,"is_oa":true,"landing_page_url":"https://hdl.handle.net/20.500.14454/2398","pdf_url":"https://deustoteka.deusto.es/bitstreams/725d0674-e9ae-4d42-a09a-273945e3673e/download","source":{"id":"https://openalex.org/S4306401525","display_name":"Basque Digital Memory (Vital Foundation)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I134113660","host_organization_name":"University of Nevada, Reno","host_organization_lineage":["https://openalex.org/I134113660"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"doctoral thesis"}],"best_oa_location":{"id":"pmh:oai:loyola.biblioteca.deusto.es:11656/28851","doi":null,"is_oa":true,"landing_page_url":"https://hdl.handle.net/20.500.14454/2398","pdf_url":"https://deustoteka.deusto.es/bitstreams/725d0674-e9ae-4d42-a09a-273945e3673e/download","source":{"id":"https://openalex.org/S4306401525","display_name":"Basque Digital Memory (Vital Foundation)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I134113660","host_organization_name":"University of Nevada, Reno","host_organization_lineage":["https://openalex.org/I134113660"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"doctoral thesis"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7080694014.pdf","grobid_xml":"https://content.openalex.org/works/W7080694014.grobid-xml"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W1191599655","https://openalex.org/W2173248099","https://openalex.org/W2531327146","https://openalex.org/W2551887912","https://openalex.org/W2736601468","https://openalex.org/W2750384547","https://openalex.org/W2757631751","https://openalex.org/W2767414122","https://openalex.org/W2898436992","https://openalex.org/W2899205164","https://openalex.org/W2902986194","https://openalex.org/W2904981516","https://openalex.org/W2935837427","https://openalex.org/W2941729817","https://openalex.org/W2951548327","https://openalex.org/W2996110979","https://openalex.org/W2997118265","https://openalex.org/W3030163527","https://openalex.org/W3041404693","https://openalex.org/W3041890730","https://openalex.org/W3095135648","https://openalex.org/W3128522352","https://openalex.org/W3178385351","https://openalex.org/W3196052105","https://openalex.org/W4200633036","https://openalex.org/W4221167530","https://openalex.org/W4226342598","https://openalex.org/W4296604211","https://openalex.org/W4313447450","https://openalex.org/W4380994478","https://openalex.org/W4387323344","https://openalex.org/W4389650579","https://openalex.org/W4405145750","https://openalex.org/W4415795831","https://openalex.org/W6893494775","https://openalex.org/W7094090683"],"related_works":["https://openalex.org/W7208079105","https://openalex.org/W3012922053","https://openalex.org/W4415796929","https://openalex.org/W4399929809","https://openalex.org/W4391117131","https://openalex.org/W3092196036","https://openalex.org/W3208763156","https://openalex.org/W7138866324","https://openalex.org/W4413244843","https://openalex.org/W3037118364"],"abstract_inverted_index":{"As":[0],"we":[1,238],"witness":[2],"the":[3,11,27,30,37,39,69,100,105,121,140,143,175,203,206,242,245,273,312],"rapid":[4],"ascent":[5],"of":[6,13,103,142,158,205,215,244,295],"artificial":[7],"intelligence,":[8],"concerns":[9],"regarding":[10],"safety":[12],"AI":[14,21],"models":[15,79,216,293],"have":[16],"significantly":[17],"heightened.":[18],"It":[19],"encompasses":[20],"alignment":[22],"and":[23,25,36,67,227,307],"robustness":[24,201],"resilience,":[26],"former":[28],"being":[29],"ability":[31,40],"to":[32,41,43,59,62,84,95,128,199,240,265,291],"withstand":[33],"unknown":[34],"scenarios":[35],"latter":[38],"adapt":[42],"such":[44,217,231],"new":[45,302],"scenarios.":[46],"All":[47],"these":[48,305],"attributes":[49],"are":[50,192,263],"becoming":[51],"essential":[52],"pillars":[53],"for":[54,146,168,282],"future":[55],"models,":[56],"which":[57,287],"need":[58,83],"be":[60,85,92],"trustworthy":[61,87],"gain":[63],"acceptance":[64],"in":[65,113,149,160],"industries":[66],"among":[68],"general":[70],"public.":[71],"In":[72],"fact,":[73],"it":[74,211],"is":[75,154,277],"increasingly":[76],"likely":[77],"that":[78,191,262,272],"will":[80],"not":[81,193],"only":[82],"inherently":[86],"but":[88],"may":[89],"also":[90],"soon":[91],"legally":[93],"required":[94],"demonstrate":[96],"this":[97,135,161,236,309],"characteristic.":[98],"Despite":[99],"critical":[101],"importance":[102],"safety,":[104],"current":[106],"research":[107],"landscape":[108],"shows":[109],"a":[110,155,183,278],"notable":[111],"deficiency":[112],"studies":[114],"focused":[115],"on":[116,177,182],"it.":[117],"However,":[118],"since":[119],"2016,":[120],"Out-of-Distribution":[122],"detection":[123,179,208,247,275],"paradigm":[124,281],"has":[125,137],"been":[126],"developed":[127],"enhance":[129],"model":[130],"robustness.":[131],"Since":[132],"its":[133,147,250],"inception,":[134],"framework":[136,248,276],"gradually":[138],"captured":[139],"attention":[141],"scientific":[144],"community":[145],"applicability":[148],"real-world":[150,267],"settings.":[151],"Today,":[152],"there":[153],"substantial":[156],"body":[157],"work":[159],"field,":[162],"with":[163],"even":[164],"official":[165],"benchmarks":[166],"established":[167],"testing":[169],"various":[170],"proposed":[171],"OoD":[172,178,207,246,274],"detectors.":[173],"Yet,":[174],"literature":[176],"predominantly":[180],"focuses":[181],"specific":[184],"task-supervised":[185],"image":[186,189],"classification-often":[187],"utilizing":[188],"datasets":[190],"particularly":[194],"complex.":[195],"This":[196,269],"Thesis":[197],"aims":[198],"investigate":[200],"through":[202],"expansion":[204],"framework.":[209],"Specifically,":[210],"explores":[212],"other":[213],"types":[214],"as":[218,232],"Spiking":[219],"Neural":[220],"Networks,":[221],"different":[222],"tasks":[223,261],"like":[224],"Object":[225],"Detection,":[226],"alternative":[228],"learning":[229],"paradigms":[230],"Reinforcement":[233],"Learning.":[234],"Through":[235],"research,":[237],"seek":[239],"broaden":[241],"scope":[243],"beyond":[249],"traditional":[251],"applications,":[252],"whether":[253],"by":[254,259],"exploring":[255],"uncharted":[256],"approaches":[257],"or":[258],"tackling":[260],"closer":[264,290],"practical":[266],"applications.":[268],"dissertation":[270],"demonstrates":[271],"highly":[279],"useful":[280],"Open":[283],"World":[284],"Machine":[285],"Learning,":[286],"brings":[288],"us":[289],"implementing":[292],"capable":[294],"learning,":[296],"recognizing":[297],"their":[298],"knowledge":[299,303,310],"gaps,":[300,306],"consolidating":[301],"from":[304],"integrating":[308],"into":[311],"model.":[313]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2025-10-10T00:00:00"}
