{"id":"https://openalex.org/W4281747917","doi":"https://doi.org/10.1162/neco_a_01513","title":"Sensitivity of Sparse Codes to Image Distortions","display_name":"Sensitivity of Sparse Codes to Image Distortions","publication_year":2022,"publication_date":"2022-06-07","ids":{"openalex":"https://openalex.org/W4281747917","doi":"https://doi.org/10.1162/neco_a_01513","pmid":"https://pubmed.ncbi.nlm.nih.gov/35671463"},"language":"en","primary_location":{"id":"doi:10.1162/neco_a_01513","is_oa":false,"landing_page_url":"https://doi.org/10.1162/neco_a_01513","pdf_url":null,"source":{"id":"https://openalex.org/S207023548","display_name":"Neural Computation","issn_l":"0899-7667","issn":["0899-7667","1530-888X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315718","host_organization_name":"The MIT Press","host_organization_lineage":["https://openalex.org/P4310315718"],"host_organization_lineage_names":["The MIT Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Computation","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5036889071","display_name":"Kyle Luther","orcid":null},"institutions":[{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Kyle Luther","raw_affiliation_strings":["Department of Physics and Neuroscience Institute, Princeton University, Princeton, NJ 08544, U.S.A. kluther@princeton.edu"],"affiliations":[{"raw_affiliation_string":"Department of Physics and Neuroscience Institute, Princeton University, Princeton, NJ 08544, U.S.A. kluther@princeton.edu","institution_ids":["https://openalex.org/I20089843"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044273339","display_name":"H. Sebastian Seung","orcid":"https://orcid.org/0000-0002-8591-6733"},"institutions":[{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"H. Sebastian Seung","raw_affiliation_strings":["Neuroscience Institute and Department of Computer Science, Princeton University, Princeton, NJ 08544, U.S.A. sseung@princeton.edu"],"affiliations":[{"raw_affiliation_string":"Neuroscience Institute and Department of Computer Science, Princeton University, Princeton, NJ 08544, U.S.A. sseung@princeton.edu","institution_ids":["https://openalex.org/I20089843"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5036889071","https://openalex.org/A5044273339"],"corresponding_institution_ids":["https://openalex.org/I20089843"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05122377,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"34","issue":"7","first_page":"1616","last_page":"1635"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10581","display_name":"Neural dynamics and brain function","score":0.9797000288963318,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9764999747276306,"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/neural-coding","display_name":"Neural coding","score":0.7914756536483765},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.7416531443595886},{"id":"https://openalex.org/keywords/k-svd","display_name":"K-SVD","score":0.7217947244644165},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.6698557734489441},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6149501204490662},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5694836974143982},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5209758877754211},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.4581742286682129},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.45399388670921326},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.42637503147125244},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.42031237483024597},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3351978063583374},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.17474833130836487},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.14427325129508972}],"concepts":[{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.7914756536483765},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.7416531443595886},{"id":"https://openalex.org/C154771677","wikidata":"https://www.wikidata.org/wiki/Q17098361","display_name":"K-SVD","level":3,"score":0.7217947244644165},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.6698557734489441},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6149501204490662},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5694836974143982},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5209758877754211},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.4581742286682129},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.45399388670921326},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.42637503147125244},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.42031237483024597},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3351978063583374},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.17474833130836487},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.14427325129508972},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016000","descriptor_name":"Cluster Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016000","descriptor_name":"Cluster Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016000","descriptor_name":"Cluster Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1162/neco_a_01513","is_oa":false,"landing_page_url":"https://doi.org/10.1162/neco_a_01513","pdf_url":null,"source":{"id":"https://openalex.org/S207023548","display_name":"Neural Computation","issn_l":"0899-7667","issn":["0899-7667","1530-888X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315718","host_organization_name":"The MIT Press","host_organization_lineage":["https://openalex.org/P4310315718"],"host_organization_lineage_names":["The MIT Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Computation","raw_type":"journal-article"},{"id":"pmid:35671463","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35671463","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural computation","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4699999988079071,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2007339694","https://openalex.org/W2015418199","https://openalex.org/W2075649259","https://openalex.org/W2087514981","https://openalex.org/W2097018403","https://openalex.org/W2100556411","https://openalex.org/W2101926813","https://openalex.org/W2105464873","https://openalex.org/W2118804867","https://openalex.org/W2122922389","https://openalex.org/W2145889472","https://openalex.org/W2152204644","https://openalex.org/W2153663612","https://openalex.org/W2162950292","https://openalex.org/W2546302380","https://openalex.org/W2559655401","https://openalex.org/W2963684088","https://openalex.org/W2990138404","https://openalex.org/W2997574889","https://openalex.org/W3035060554","https://openalex.org/W3035524453","https://openalex.org/W3108837972","https://openalex.org/W3134652006","https://openalex.org/W4231421859","https://openalex.org/W4247541366","https://openalex.org/W6640963894","https://openalex.org/W6674764012","https://openalex.org/W6681096077","https://openalex.org/W6685352114","https://openalex.org/W6774314701","https://openalex.org/W6784947832","https://openalex.org/W6791742336","https://openalex.org/W6968397192"],"related_works":["https://openalex.org/W2016265625","https://openalex.org/W2111634407","https://openalex.org/W2552089492","https://openalex.org/W2982240858","https://openalex.org/W4205656132","https://openalex.org/W2008821896","https://openalex.org/W2067062989","https://openalex.org/W3004790527","https://openalex.org/W2972860561","https://openalex.org/W634011990"],"abstract_inverted_index":{"Sparse":[0],"coding":[1],"has":[2],"been":[3],"proposed":[4],"as":[5,12],"a":[6,37,83,87,109,113,123],"theory":[7],"of":[8,58,61,91,126,134],"visual":[9],"cortex":[10],"and":[11,129],"an":[13],"unsupervised":[14],"algorithm":[15],"for":[16],"learning":[17],"representations.":[18],"We":[19],"show":[20],"empirically":[21],"with":[22,65,86],"the":[23,51,56],"MNIST":[24],"data":[25],"set":[26],"that":[27,39,50],"sparse":[28,77,94,127,139],"codes":[29,78,95,140],"can":[30],"be":[31,122,132],"very":[32],"sensitive":[33],"to":[34,55,73,98,118,121,141],"image":[35],"distortions,":[36],"behavior":[38],"may":[40],"hinder":[41],"invariant":[42,142],"object":[43,143],"recognition.":[44,144],"A":[45,68],"locally":[46],"linear":[47,59,84],"analysis":[48],"suggests":[49],"sensitivity":[52],"is":[53,71],"due":[54],"existence":[57],"combinations":[60],"active":[62],"dictionary":[63],"elements":[64],"high":[66],"cancellation.":[67],"nearest-neighbor":[69],"classifier":[70,85],"shown":[72,97],"perform":[74],"worse":[75],"on":[76],"than":[79,102,108],"original":[80,103],"images.":[81],"For":[82],"sufficiently":[88],"large":[89],"number":[90],"labeled":[92],"examples,":[93],"are":[96],"yield":[99],"higher":[100,107],"accuracy":[101],"images,":[104],"but":[105],"no":[106],"representation":[110],"computed":[111],"by":[112],"random":[114],"feedforward":[115],"net.":[116],"Sensitivity":[117],"distortions":[119],"seems":[120],"basic":[124],"property":[125,136],"codes,":[128],"one":[130],"should":[131],"aware":[133],"this":[135],"when":[137],"applying":[138]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
