{"id":"https://openalex.org/W3050342786","doi":"https://doi.org/10.1109/icip40778.2020.9190679","title":"Gradients as a Measure of Uncertainty in Neural Networks","display_name":"Gradients as a Measure of Uncertainty in Neural Networks","publication_year":2020,"publication_date":"2020-09-30","ids":{"openalex":"https://openalex.org/W3050342786","doi":"https://doi.org/10.1109/icip40778.2020.9190679","mag":"3050342786"},"language":"en","primary_location":{"id":"doi:10.1109/icip40778.2020.9190679","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip40778.2020.9190679","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2008.08030","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074029439","display_name":"Jin-Sol Lee","orcid":"https://orcid.org/0000-0001-8749-7651"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jinsol Lee","raw_affiliation_strings":["OLIVES at the Center for Signal and Information Processing, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA","Georgia Institute of Technology,OLIVES at the Center for Signal and Information Processing School of Electrical and Computer Engineering,Atlanta,GA,30332-0250"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"OLIVES at the Center for Signal and Information Processing, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"Georgia Institute of Technology,OLIVES at the Center for Signal and Information Processing School of Electrical and Computer Engineering,Atlanta,GA,30332-0250","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006145139","display_name":"Ghassan AlRegib","orcid":"https://orcid.org/0000-0001-6818-8001"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ghassan AlRegib","raw_affiliation_strings":["OLIVES at the Center for Signal and Information Processing, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA","Georgia Institute of Technology,OLIVES at the Center for Signal and Information Processing School of Electrical and Computer Engineering,Atlanta,GA,30332-0250"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"OLIVES at the Center for Signal and Information Processing, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"Georgia Institute of Technology,OLIVES at the Center for Signal and Information Processing School of Electrical and Computer Engineering,Atlanta,GA,30332-0250","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.09501798,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"2416","last_page":"2420"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":1.0,"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":1.0,"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":0.9991999864578247,"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":0.9987999796867371,"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/computer-science","display_name":"Computer science","score":0.7590945959091187},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.7589198350906372},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6543476581573486},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6256856322288513},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.5483154654502869},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5403050184249878},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.4619801938533783},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2861536741256714}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7590945959091187},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.7589198350906372},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6543476581573486},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6256856322288513},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.5483154654502869},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5403050184249878},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.4619801938533783},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2861536741256714},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/icip40778.2020.9190679","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip40778.2020.9190679","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2008.08030","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2008.08030","pdf_url":"https://arxiv.org/pdf/2008.08030","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"mag:3050342786","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2008.08030","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2008.08030","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2008.08030","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":"article"},{"id":"doi:10.17023/777v-wp54","is_oa":true,"landing_page_url":"https://doi.org/10.17023/777v-wp54","pdf_url":null,"source":{"id":"https://openalex.org/S7407051697","display_name":"IEEE RESOURCE CENTERS","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2008.08030","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2008.08030","pdf_url":"https://arxiv.org/pdf/2008.08030","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3050342786.pdf","grobid_xml":"https://content.openalex.org/works/W3050342786.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W967544008","https://openalex.org/W2108598243","https://openalex.org/W2112796928","https://openalex.org/W2194775991","https://openalex.org/W2335728318","https://openalex.org/W2600383743","https://openalex.org/W2613718673","https://openalex.org/W2767414122","https://openalex.org/W2775799392","https://openalex.org/W2786712888","https://openalex.org/W2867167548","https://openalex.org/W2897009419","https://openalex.org/W2899748887","https://openalex.org/W2946417913","https://openalex.org/W2952053192","https://openalex.org/W2963060032","https://openalex.org/W2963207607","https://openalex.org/W2964212410","https://openalex.org/W2970446076","https://openalex.org/W3118608800","https://openalex.org/W6620707391","https://openalex.org/W6625168331","https://openalex.org/W6640425456","https://openalex.org/W6703116779","https://openalex.org/W6728622933","https://openalex.org/W6735443497","https://openalex.org/W6739651123","https://openalex.org/W6745891213","https://openalex.org/W6747438826","https://openalex.org/W6748163547","https://openalex.org/W6752760542","https://openalex.org/W6757555829"],"related_works":["https://openalex.org/W3090434739","https://openalex.org/W2939992774","https://openalex.org/W1574328159","https://openalex.org/W3127876718","https://openalex.org/W3089920065","https://openalex.org/W4226365483","https://openalex.org/W2356488156","https://openalex.org/W3189096860","https://openalex.org/W2107725879","https://openalex.org/W289666278","https://openalex.org/W2899135085","https://openalex.org/W2949017160","https://openalex.org/W2913832605","https://openalex.org/W3105663403","https://openalex.org/W3038052560","https://openalex.org/W2074574036","https://openalex.org/W2945122416","https://openalex.org/W2892722976","https://openalex.org/W2991873520","https://openalex.org/W2126705763"],"abstract_inverted_index":{"Despite":[0],"tremendous":[1],"success":[2],"of":[3,39,50,57,74,82,112,117,122,144],"modern":[4],"neural":[5,40,61],"networks,":[6],"they":[7],"are":[8],"known":[9],"to":[10,27,66,70,87,142],"be":[11],"overconfident":[12],"even":[13],"when":[14],"the":[15,47,72,79,102,106,110],"model":[16,86,103,118],"encounters":[17],"inputs":[18,24],"with":[19],"unfamiliar":[20,124],"conditions.":[21],"Detecting":[22],"such":[23],"is":[25,104],"vital":[26],"preventing":[28],"models":[29],"from":[30],"making":[31],"naive":[32],"predictions":[33],"that":[34,133],"may":[35],"jeopardize":[36],"real-world":[37],"applications":[38,121],"networks.":[41,62],"In":[42],"this":[43],"paper,":[44],"we":[45,64],"address":[46],"challenging":[48],"problem":[49],"devising":[51],"a":[52,85,94,115],"simple":[53],"yet":[54],"effective":[55],"measure":[56,116],"uncertainty":[58,73,119],"in":[59,120,147,152],"deep":[60],"Specifically,":[63],"propose":[65],"utilize":[67],"backpropagated":[68],"gradients":[69,113],"quantify":[71],"trained":[75],"models.":[76],"Gradients":[77],"depict":[78],"required":[80],"amount":[81],"change":[83],"for":[84],"properly":[88],"represent":[89],"given":[90],"inputs,":[91,125],"thus":[92],"providing":[93],"valuable":[95],"insight":[96],"into":[97],"how":[98],"familiar":[99],"and":[100,128,150],"certain":[101],"regarding":[105],"inputs.":[107],"We":[108,131],"demonstrate":[109],"effectiveness":[111],"as":[114],"detecting":[123],"including":[126],"out-of-distribution":[127,148],"corrupted":[129,153],"samples.":[130],"show":[132],"our":[134],"gradient-based":[135],"method":[136],"outperforms":[137],"state-of-the-art":[138],"methods":[139],"by":[140],"up":[141],"4.8%":[143],"AUROC":[145],"score":[146],"detection":[149],"35.7%":[151],"input":[154],"detection.":[155]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
