{"id":"https://openalex.org/W3121012363","doi":"https://doi.org/10.1109/ssci47803.2020.9308551","title":"Autoencoder latent space: an empirical study","display_name":"Autoencoder latent space: an empirical study","publication_year":2020,"publication_date":"2020-12-01","ids":{"openalex":"https://openalex.org/W3121012363","doi":"https://doi.org/10.1109/ssci47803.2020.9308551","mag":"3121012363"},"language":"en","primary_location":{"id":"doi:10.1109/ssci47803.2020.9308551","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssci47803.2020.9308551","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Symposium Series on Computational Intelligence (SSCI)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"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/A5086314316","display_name":"Leticia V. N. Lapenda","orcid":null},"institutions":[{"id":"https://openalex.org/I71437568","display_name":"Universidade de Pernambuco","ror":"https://ror.org/00gtcbp88","country_code":"BR","type":"education","lineage":["https://openalex.org/I71437568"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Leticia V. N. Lapenda","raw_affiliation_strings":["Computer Engineering department, University of Pernambuco (UPE), Brazil"],"affiliations":[{"raw_affiliation_string":"Computer Engineering department, University of Pernambuco (UPE), Brazil","institution_ids":["https://openalex.org/I71437568"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054750563","display_name":"Rodrigo de Paula Monteiro","orcid":"https://orcid.org/0000-0002-2423-5088"},"institutions":[{"id":"https://openalex.org/I25112270","display_name":"Universidade Federal de Pernambuco","ror":"https://ror.org/047908t24","country_code":"BR","type":"education","lineage":["https://openalex.org/I25112270"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Rodrigo P. Monteiro","raw_affiliation_strings":["Electrical Engineering department, Federal University of Pernambuco (UFPE), Brazil"],"affiliations":[{"raw_affiliation_string":"Electrical Engineering department, Federal University of Pernambuco (UFPE), Brazil","institution_ids":["https://openalex.org/I25112270"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028876161","display_name":"Carmelo J. A. Bastos-Filho","orcid":"https://orcid.org/0000-0002-0924-5341"},"institutions":[{"id":"https://openalex.org/I71437568","display_name":"Universidade de Pernambuco","ror":"https://ror.org/00gtcbp88","country_code":"BR","type":"education","lineage":["https://openalex.org/I71437568"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Carmelo J. A. Bastos-Filho","raw_affiliation_strings":["Computer Engineering department, University of Pernambuco (UPE), Brazil"],"affiliations":[{"raw_affiliation_string":"Computer Engineering department, University of Pernambuco (UPE), Brazil","institution_ids":["https://openalex.org/I71437568"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5086314316"],"corresponding_institution_ids":["https://openalex.org/I71437568"],"apc_list":null,"apc_paid":null,"fwci":0.1326,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.57690998,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2453","last_page":"2460"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9997000098228455,"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/T10320","display_name":"Neural Networks and Applications","score":0.9997000098228455,"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/T10057","display_name":"Face and Expression Recognition","score":0.9897000193595886,"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":0.9891999959945679,"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/autoencoder","display_name":"Autoencoder","score":0.7550172805786133},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.7478542923927307},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.7045624852180481},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6960912942886353},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.554955005645752},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5304044485092163},{"id":"https://openalex.org/keywords/latent-variable","display_name":"Latent variable","score":0.5257761478424072},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4917915165424347},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.4884852170944214},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.478742778301239},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.46885523200035095},{"id":"https://openalex.org/keywords/kullback\u2013leibler-divergence","display_name":"Kullback\u2013Leibler divergence","score":0.439314603805542},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.41484585404396057},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32653898000717163},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0825330913066864}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.7550172805786133},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.7478542923927307},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.7045624852180481},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6960912942886353},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.554955005645752},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5304044485092163},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.5257761478424072},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4917915165424347},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4884852170944214},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.478742778301239},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.46885523200035095},{"id":"https://openalex.org/C171752962","wikidata":"https://www.wikidata.org/wiki/Q255166","display_name":"Kullback\u2013Leibler divergence","level":2,"score":0.439314603805542},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.41484585404396057},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32653898000717163},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0825330913066864},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ssci47803.2020.9308551","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssci47803.2020.9308551","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Symposium Series on Computational Intelligence (SSCI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1486203010","https://openalex.org/W1493357981","https://openalex.org/W2087016914","https://openalex.org/W2090922444","https://openalex.org/W2750384547","https://openalex.org/W2778685442","https://openalex.org/W2913796826","https://openalex.org/W2921787039","https://openalex.org/W2983948788","https://openalex.org/W2989630177","https://openalex.org/W2990294637","https://openalex.org/W3005116366","https://openalex.org/W3011249019","https://openalex.org/W3034782902","https://openalex.org/W3102094077","https://openalex.org/W3118608800","https://openalex.org/W3147354744","https://openalex.org/W4288623594","https://openalex.org/W6743688258","https://openalex.org/W6759195315","https://openalex.org/W6770261585","https://openalex.org/W6773736450","https://openalex.org/W6787972765","https://openalex.org/W6855462042"],"related_works":["https://openalex.org/W2772780115","https://openalex.org/W2592385986","https://openalex.org/W2785535669","https://openalex.org/W2966657595","https://openalex.org/W4281924768","https://openalex.org/W4289653936","https://openalex.org/W1576462183","https://openalex.org/W2775464024","https://openalex.org/W2158785961","https://openalex.org/W3121012363"],"abstract_inverted_index":{"Feature":[0],"extraction":[1],"is":[2,13,48,98],"essential":[3],"to":[4,15,45,84,92],"many":[5,63],"machine":[6],"learning":[7],"tasks.":[8],"By":[9],"extracting":[10],"features,":[11],"it":[12],"possible":[14,143],"reduce":[16],"the":[17,23,49,54,59,68,77,85,94,99,110,115,122,126,133,146,149,170],"dimensionality":[18],"of":[19,74],"datasets,":[20],"focusing":[21],"on":[22,66,109,169],"most":[24],"relevant":[25],"features":[26],"and":[27,131,148,161],"minimizing":[28],"redundancy.":[29],"Autoencoders":[30],"(AE)":[31],"are":[32,80],"neural":[33],"network":[34],"architectures":[35],"commonly":[36],"used":[37,44,136],"for":[38,137,158],"feature":[39],"extraction.":[40],"A":[41],"usual":[42],"metric":[43],"evaluate":[46],"AEs":[47],"reconstruction":[50,86,150],"error,":[51,87],"which":[52],"compares":[53],"AE":[55,111,123,127,171],"output":[56],"data":[57,134],"with":[58],"original":[60],"one.":[61],"However,":[62],"applications":[64],"depend":[65],"how":[67,106],"input":[69],"representations":[70],"in":[71],"intermediate":[72],"layers":[73],"AEs,":[75],"i.e.":[76,166],"latent":[78,95,164],"variables,":[79,165],"distributed.":[81],"Therefore,":[82],"additionally":[83],"an":[88],"interesting":[89],"measure":[90],"-":[91,97],"study":[93],"variables":[96],"Kullback-Leibler":[100],"divergence":[101],"(KLD).":[102],"This":[103],"work":[104],"analyzes":[105],"some":[107],"variations":[108,119],"training":[112],"process":[113],"impact":[114],"aforementioned":[116],"measures.":[117],"Those":[118],"are:":[120],"1.":[121],"depth,":[124],"2.":[125],"middle":[128,172],"layer":[129],"architecture,":[130],"3.":[132],"setup":[135],"training.":[138],"Results":[139],"have":[140,156],"shown":[141],"a":[142],"relation":[144],"between":[145],"KLD":[147],"error.":[151],"In":[152],"fact,":[153],"lower":[154],"errors":[155],"happened":[157],"higher":[159],"KLDs":[160],"less":[162],"compressed":[163],"more":[167],"neurons":[168],"layers.":[173]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
