{"id":"https://openalex.org/W3165542889","doi":null,"title":"Blurs Make Results Clearer: Spatial Smoothings to Improve Accuracy, Uncertainty, and Robustness","display_name":"Blurs Make Results Clearer: Spatial Smoothings to Improve Accuracy, Uncertainty, and Robustness","publication_year":2021,"publication_date":"2021-05-26","ids":{"openalex":"https://openalex.org/W3165542889","mag":"3165542889"},"language":"en","primary_location":{"id":"mag:3165542889","doi":null,"is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2105.12639","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,"listed_in":[],"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},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://export.arxiv.org/pdf/2105.12639","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5019224758","display_name":"Namuk Park","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Namuk Park","raw_affiliation_strings":[", Yonsei University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":", Yonsei University","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075315705","display_name":"Songkuk Kim","orcid":"https://orcid.org/0000-0003-4147-4627","observed_orcids":["https://orcid.org/0000-0003-4147-4627"]},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Songkuk Kim","raw_affiliation_strings":[", Yonsei University"],"raw_orcid":"https://orcid.org/0000-0003-4147-4627","affiliations":[{"raw_affiliation_string":", Yonsei University","institution_ids":["https://openalex.org/I193775966"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I193775966"],"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":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.36230000853538513,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.36230000853538513,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.33500000834465027,"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":0.2639000117778778,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/spatial-smoothing","display_name":"spatial smoothing","score":0.8059999942779541},{"id":"https://openalex.org/keywords/bayesian-neural-networks","display_name":"Bayesian neural networks","score":0.9269999861717224},{"id":"https://openalex.org/keywords/uncertainty-estimation","display_name":"uncertainty estimation","score":0.8970000147819519},{"id":"https://openalex.org/keywords/robustness","display_name":"robustness","score":0.847000002861023},{"id":"https://openalex.org/keywords/ensemble-size","display_name":"ensemble size","score":0.47999998927116394},{"id":"https://openalex.org/keywords/global-average-pooling","display_name":"global average pooling","score":0.8090000152587891},{"id":"https://openalex.org/keywords/pre-activation","display_name":"pre-activation","score":0.9559999704360962},{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.7400000095367432},{"id":"https://openalex.org/keywords/computational-cost-reduction","display_name":"computational complexity reduction","score":0.5210000276565552}],"concepts":[{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.9017155170440674},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7919334173202515},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.7210807800292969},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6923686265945435},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5028697848320007},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4949337840080261},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42979252338409424},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36354804039001465},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34993135929107666},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.34219640493392944},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20232203602790833},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.10108682513237},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:3165542889","doi":null,"is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2105.12639","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,"listed_in":[],"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}],"best_oa_location":{"id":"mag:3165542889","doi":null,"is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2105.12639","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,"listed_in":[],"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},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W582134693","https://openalex.org/W1686810756","https://openalex.org/W1719489212","https://openalex.org/W1799366690","https://openalex.org/W1901129140","https://openalex.org/W1913356549","https://openalex.org/W2103328396","https://openalex.org/W2194775991","https://openalex.org/W2295107390","https://openalex.org/W2302255633","https://openalex.org/W2548077621","https://openalex.org/W2549139847","https://openalex.org/W2560321925","https://openalex.org/W2600383743","https://openalex.org/W2622263826","https://openalex.org/W2626778328","https://openalex.org/W2626967530","https://openalex.org/W2807007689","https://openalex.org/W2907020378","https://openalex.org/W2913314773","https://openalex.org/W2945033152","https://openalex.org/W2948194985","https://openalex.org/W2956805085","https://openalex.org/W2962933129","https://openalex.org/W2963060032","https://openalex.org/W2963091558","https://openalex.org/W2963163009","https://openalex.org/W2963215553","https://openalex.org/W2963399222","https://openalex.org/W2964121937","https://openalex.org/W2964137095","https://openalex.org/W2966299821","https://openalex.org/W2967597807","https://openalex.org/W2992525328","https://openalex.org/W2992693735","https://openalex.org/W2994797252","https://openalex.org/W3007700590","https://openalex.org/W3030520226","https://openalex.org/W3034402660","https://openalex.org/W3034666242","https://openalex.org/W3094502228","https://openalex.org/W3107291594","https://openalex.org/W3116489684","https://openalex.org/W3118608800","https://openalex.org/W3126857817","https://openalex.org/W3145185940","https://openalex.org/W3173605386"],"related_works":["https://openalex.org/W4285580224","https://openalex.org/W4200632698","https://openalex.org/W4402727286","https://openalex.org/W3147091064","https://openalex.org/W7103509932","https://openalex.org/W7052460430","https://openalex.org/W4402425186","https://openalex.org/W2918710116","https://openalex.org/W4390041895","https://openalex.org/W3112594655"],"abstract_inverted_index":{"Bayesian":[0,24],"neural":[1,121],"networks":[2,122],"(BNNs)":[3],"have":[4],"shown":[5],"success":[6],"in":[7,22,41,195],"the":[8,70,76,98,125,133,139,144,174,191,196,200],"areas":[9],"of":[10,30,60,85,91,109,129,143,173],"uncertainty":[11,81,185],"estimation":[12,186],"and":[13,83,141,163,187],"robustness.":[14],"However,":[15],"a":[16,27,38,52,65,88,107,151],"crucial":[17],"challenge":[18],"prohibits":[19],"their":[20],"use":[21],"practice:":[23],"NNs":[25],"require":[26],"large":[28],"number":[29,128],"predictions":[31],"to":[32,37,69,118,123,138,168],"produce":[33],"reliable":[34],"results,":[35],"leading":[36],"significant":[39],"increase":[40],"computational":[42],"cost.":[43],"To":[44],"alleviate":[45],"this":[46,112,208],"issue,":[47],"we":[48,72,149],"propose":[49],"spatial":[50,77,99,175,201],"smoothing,":[51],"method":[53,113],"that":[54,75,132],"ensembles":[55],"neighboring":[56],"feature":[57],"map":[58],"points":[59],"CNNs.":[61],"By":[62],"simply":[63],"adding":[64],"few":[66],"blur":[67],"layers":[68],"models,":[71],"empirically":[73],"show":[74],"smoothing":[78,100,140],"improves":[79],"accuracy,":[80,181],"estimation,":[82],"robustness":[84,188],"BNNs":[86,96],"across":[87],"whole":[89],"range":[90],"ensemble":[92],"sizes.":[93],"In":[94,147],"particular,":[95],"incorporating":[97],"achieve":[101],"high":[102],"predictive":[103],"performance":[104],"merely":[105],"with":[106],"handful":[108],"ensembles.":[110],"Moreover,":[111],"also":[114,183],"can":[115,135],"be":[116,136],"applied":[117],"canonical":[119],"deterministic":[120],"improve":[124,184],"performances.":[126],"A":[127],"evidences":[130],"suggest":[131],"improvements":[134],"attributed":[137],"flattening":[142],"loss":[145,192],"landscape.":[146],"addition,":[148],"provide":[150],"fundamental":[152],"explanation":[153],"for":[154],"prior":[155],"works":[156],"-":[157,165],"namely,":[158],"global":[159],"average":[160],"pooling,":[161],"pre-activation,":[162],"ReLU6":[164],"by":[166,189],"addressing":[167],"them":[169],"as":[170,199],"special":[171],"cases":[172],"smoothing.":[176,202],"These":[177],"not":[178],"only":[179],"enhance":[180],"but":[182],"making":[190],"landscape":[193],"smoother":[194],"same":[197],"manner":[198],"The":[203],"code":[204],"is":[205],"available":[206],"at":[207],"https":[209],"URL.":[210]},"counts_by_year":[],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2021-06-07T00:00:00"}