{"id":"https://openalex.org/W4224839115","doi":"https://doi.org/10.1142/s0218001422550059","title":"Mutual Information Variational Autoencoders and Its Application to Feature Extraction of Multivariate Time Series","display_name":"Mutual Information Variational Autoencoders and Its Application to Feature Extraction of Multivariate Time Series","publication_year":2022,"publication_date":"2022-04-23","ids":{"openalex":"https://openalex.org/W4224839115","doi":"https://doi.org/10.1142/s0218001422550059"},"language":"en","primary_location":{"id":"doi:10.1142/s0218001422550059","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001422550059","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-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/A5091257628","display_name":"Junying Li","orcid":"https://orcid.org/0000-0002-7286-6327"},"institutions":[{"id":"https://openalex.org/I4210092944","display_name":"Dalian University","ror":"https://ror.org/00g2ypp58","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210092944"]},{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junying Li","raw_affiliation_strings":["Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024, China","institution_ids":["https://openalex.org/I4210092944","https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015696755","display_name":"Weijie Ren","orcid":"https://orcid.org/0000-0002-2711-8813"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weijie Ren","raw_affiliation_strings":["College of Automation, Harbin Engineering University, Harbin 150001, China"],"affiliations":[{"raw_affiliation_string":"College of Automation, Harbin Engineering University, Harbin 150001, China","institution_ids":["https://openalex.org/I151727225"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032636287","display_name":"Min Han","orcid":"https://orcid.org/0000-0002-2964-4884"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Min Han","raw_affiliation_strings":["Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education, Dalian University of Technology, Dalian 116024, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education, Dalian University of Technology, Dalian 116024, China","institution_ids":["https://openalex.org/I27357992"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5032636287"],"corresponding_institution_ids":["https://openalex.org/I27357992"],"apc_list":null,"apc_paid":null,"fwci":1.0411,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.74338446,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"36","issue":"06","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.9909999966621399,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.9855999946594238,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/mutual-information","display_name":"Mutual information","score":0.7434365749359131},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7114299535751343},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6522126197814941},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.6455671787261963},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5246603488922119},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.501953125},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.4770566523075104},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4750761389732361},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.472277969121933},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.43550407886505127},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.42940929532051086},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41684508323669434}],"concepts":[{"id":"https://openalex.org/C152139883","wikidata":"https://www.wikidata.org/wiki/Q252973","display_name":"Mutual information","level":2,"score":0.7434365749359131},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7114299535751343},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6522126197814941},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.6455671787261963},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5246603488922119},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.501953125},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.4770566523075104},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4750761389732361},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.472277969121933},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.43550407886505127},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.42940929532051086},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41684508323669434},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0218001422550059","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001422550059","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/1","display_name":"No poverty","score":0.6800000071525574}],"awards":[{"id":"https://openalex.org/G6735171862","display_name":null,"funder_award_id":"DUT20LAB114","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G876797204","display_name":null,"funder_award_id":"61773087","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W2000904666","https://openalex.org/W2004203760","https://openalex.org/W2069508080","https://openalex.org/W2074477564","https://openalex.org/W2089468765","https://openalex.org/W2117829824","https://openalex.org/W2172064003","https://openalex.org/W2195453971","https://openalex.org/W2280154071","https://openalex.org/W2285130932","https://openalex.org/W2302719757","https://openalex.org/W2531022405","https://openalex.org/W2611975175","https://openalex.org/W2737392365","https://openalex.org/W2758567761","https://openalex.org/W2775631786","https://openalex.org/W2782945673","https://openalex.org/W2789699400","https://openalex.org/W2793890360","https://openalex.org/W2796072231","https://openalex.org/W2892709813","https://openalex.org/W2893754789","https://openalex.org/W2910027896","https://openalex.org/W2918076989","https://openalex.org/W2921144944","https://openalex.org/W2945532623","https://openalex.org/W2949419896","https://openalex.org/W2962940008","https://openalex.org/W2963188732","https://openalex.org/W2987702431","https://openalex.org/W2988153729","https://openalex.org/W3007441389","https://openalex.org/W3105208235","https://openalex.org/W3121607534"],"related_works":["https://openalex.org/W2905433371","https://openalex.org/W4361193272","https://openalex.org/W4310278675","https://openalex.org/W2806259446","https://openalex.org/W2963326959","https://openalex.org/W4311431240","https://openalex.org/W4312407344","https://openalex.org/W4384115502","https://openalex.org/W4226258012","https://openalex.org/W4383681494"],"abstract_inverted_index":{"The":[0,62,98,119],"application":[1],"of":[2,24,37,46,57,75,96,104,133,154,159],"deep":[3,17],"learning":[4],"in":[5,152],"time-series":[6,59,113],"prediction":[7],"has":[8],"developed":[9],"gradually.":[10],"In":[11,34,77],"this":[12],"paper,":[13],"we":[14,41,79],"propose":[15],"a":[16,68,81,116],"generative":[18],"network":[19],"model":[20,136,145],"for":[21,48,111],"feature":[22,49,69],"extraction":[23],"multivariate":[25,58,112],"time":[26,126],"series,":[27],"namely,":[28],"mutual":[29,82,107],"information":[30,83],"variational":[31],"autoencoders":[32],"(MI-VAE).":[33],"the":[35,38,43,54,86,91,102,134,143],"architecture":[36],"proposed":[39,99,135,144],"model,":[40,100],"use":[42],"latent":[44,63,160],"space":[45,64],"VAE":[47,105],"learning,":[50],"which":[51,89],"can":[52,71],"extract":[53],"essential":[55],"features":[56,110],"data":[60,114],"effectively.":[61],"employed":[65],"directly":[66],"as":[67],"extractor":[70],"avoid":[72],"poor":[73],"interpretability":[74],"model.":[76,97],"addition,":[78],"introduce":[80],"term":[84],"into":[85],"loss":[87],"function,":[88],"improves":[90],"expression":[92,157],"capability":[93,158],"and":[94,106,122,137,156],"accuracy":[95,155],"combining":[101],"merits":[103],"information,":[108],"extracts":[109],"from":[115],"new":[117],"perspective.":[118],"Lorenz":[120],"system":[121],"Beijing":[123],"air":[124],"quality":[125],"series":[127],"are":[128],"used":[129],"to":[130,148],"test":[131],"performance":[132],"comparative":[138],"models.":[139],"Results":[140],"show":[141],"that":[142],"is":[146],"superior":[147],"other":[149],"similar":[150],"models":[151],"terms":[153],"space.":[161]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
