{"id":"https://openalex.org/W4396535339","doi":"https://doi.org/10.1109/tnnls.2024.3384842","title":"Distributional Drift Adaptation With Temporal Conditional Variational Autoencoder for Multivariate Time Series Forecasting","display_name":"Distributional Drift Adaptation With Temporal Conditional Variational Autoencoder for Multivariate Time Series Forecasting","publication_year":2024,"publication_date":"2024-04-29","ids":{"openalex":"https://openalex.org/W4396535339","doi":"https://doi.org/10.1109/tnnls.2024.3384842","pmid":"https://pubmed.ncbi.nlm.nih.gov/38683706"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2024.3384842","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2024.3384842","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","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/A5050350085","display_name":"Hui He","orcid":"https://orcid.org/0000-0001-5515-2739"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hui He","raw_affiliation_strings":["School of Medical Technology, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-5515-2739","affiliations":[{"raw_affiliation_string":"School of Medical Technology, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100784844","display_name":"Qi Zhang","orcid":"https://orcid.org/0000-0002-1037-1361"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Zhang","raw_affiliation_strings":["School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-1037-1361","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102950239","display_name":"Kun Yi","orcid":"https://orcid.org/0000-0002-9980-6033"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kun Yi","raw_affiliation_strings":["School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-9980-6033","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034376285","display_name":"Kaize Shi","orcid":"https://orcid.org/0000-0003-3561-3627"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Kaize Shi","raw_affiliation_strings":["Data Science and Machine Intelligence Laboratory, University of Technology Sydney, Sydney, NSW, Australia"],"raw_orcid":"https://orcid.org/0000-0003-3561-3627","affiliations":[{"raw_affiliation_string":"Data Science and Machine Intelligence Laboratory, University of Technology Sydney, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082774439","display_name":"Zhendong Niu","orcid":"https://orcid.org/0000-0002-0576-7572"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhendong Niu","raw_affiliation_strings":["School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0576-7572","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000798681","display_name":"Longbing Cao","orcid":"https://orcid.org/0000-0003-1562-9429"},"institutions":[{"id":"https://openalex.org/I99043593","display_name":"Macquarie University","ror":"https://ror.org/01sf06y89","country_code":"AU","type":"education","lineage":["https://openalex.org/I99043593"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Longbing Cao","raw_affiliation_strings":["DataX Research Centre, School of Computing, Macquarie University, Sydney, NSW, Australia","School of Computing, DataX Research Centre, Macquarie University, Sydney, NSW, Australia"],"raw_orcid":"https://orcid.org/0000-0003-1562-9429","affiliations":[{"raw_affiliation_string":"DataX Research Centre, School of Computing, Macquarie University, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I99043593"]},{"raw_affiliation_string":"School of Computing, DataX Research Centre, Macquarie University, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I99043593"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.9124,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.97137637,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"36","issue":"4","first_page":"7287","last_page":"7301"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9988999962806702,"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":0.9988999962806702,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9940999746322632,"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/T11490","display_name":"Hydrological Forecasting Using AI","score":0.9904000163078308,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental 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":0.6596086025238037},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.6168659329414368},{"id":"https://openalex.org/keywords/conditional-probability-distribution","display_name":"Conditional probability distribution","score":0.5565807819366455},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5060092806816101},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4676016867160797},{"id":"https://openalex.org/keywords/concept-drift","display_name":"Concept drift","score":0.44880419969558716},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.44405147433280945},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4356550872325897},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.41087931394577026},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.395536333322525},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36635681986808777},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.28125905990600586},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.26398128271102905},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17074227333068848},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.13379573822021484}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6596086025238037},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.6168659329414368},{"id":"https://openalex.org/C43555835","wikidata":"https://www.wikidata.org/wiki/Q2300258","display_name":"Conditional probability distribution","level":2,"score":0.5565807819366455},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5060092806816101},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4676016867160797},{"id":"https://openalex.org/C60777511","wikidata":"https://www.wikidata.org/wiki/Q3045002","display_name":"Concept drift","level":3,"score":0.44880419969558716},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.44405147433280945},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4356550872325897},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.41087931394577026},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.395536333322525},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36635681986808777},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.28125905990600586},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.26398128271102905},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17074227333068848},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.13379573822021484},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"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":2,"locations":[{"id":"doi:10.1109/tnnls.2024.3384842","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2024.3384842","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:38683706","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38683706","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":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Climate action","score":0.7900000214576721,"id":"https://metadata.un.org/sdg/13"}],"awards":[{"id":"https://openalex.org/G3883314779","display_name":null,"funder_award_id":"2019YFB1406302","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G8023270376","display_name":null,"funder_award_id":"62272048","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/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":77,"referenced_works":["https://openalex.org/W2113207826","https://openalex.org/W2560647685","https://openalex.org/W2579393094","https://openalex.org/W2604847698","https://openalex.org/W2744043447","https://openalex.org/W2756203131","https://openalex.org/W2890096158","https://openalex.org/W2962717182","https://openalex.org/W2963121266","https://openalex.org/W2963122061","https://openalex.org/W2965341826","https://openalex.org/W2970327629","https://openalex.org/W2972862002","https://openalex.org/W2980537499","https://openalex.org/W2981848865","https://openalex.org/W2988226917","https://openalex.org/W2995310170","https://openalex.org/W2997896107","https://openalex.org/W3041929891","https://openalex.org/W3047371217","https://openalex.org/W3080253043","https://openalex.org/W3082281389","https://openalex.org/W3093074257","https://openalex.org/W3121975202","https://openalex.org/W3122253332","https://openalex.org/W3154508774","https://openalex.org/W3156420331","https://openalex.org/W3158956987","https://openalex.org/W3166508292","https://openalex.org/W3175177406","https://openalex.org/W3175895678","https://openalex.org/W3176196442","https://openalex.org/W3188436598","https://openalex.org/W3189405723","https://openalex.org/W3199148273","https://openalex.org/W3207999419","https://openalex.org/W3209387005","https://openalex.org/W3211310242","https://openalex.org/W3213754079","https://openalex.org/W3215233361","https://openalex.org/W4205650351","https://openalex.org/W4221145213","https://openalex.org/W4283805364","https://openalex.org/W4285157836","https://openalex.org/W4289533938","https://openalex.org/W4382239049","https://openalex.org/W4382239131","https://openalex.org/W4385338584","https://openalex.org/W4385565288","https://openalex.org/W4387623852","https://openalex.org/W4388408951","https://openalex.org/W4388430464","https://openalex.org/W4393041492","https://openalex.org/W4401336871","https://openalex.org/W6730160768","https://openalex.org/W6752513430","https://openalex.org/W6754818960","https://openalex.org/W6757064203","https://openalex.org/W6757925885","https://openalex.org/W6762250955","https://openalex.org/W6767610075","https://openalex.org/W6771861442","https://openalex.org/W6773967291","https://openalex.org/W6780221082","https://openalex.org/W6786152982","https://openalex.org/W6786852218","https://openalex.org/W6789743973","https://openalex.org/W6789828638","https://openalex.org/W6796464841","https://openalex.org/W6797155008","https://openalex.org/W6803671390","https://openalex.org/W6810175454","https://openalex.org/W6810637551","https://openalex.org/W6846376059","https://openalex.org/W6858342418","https://openalex.org/W6858721613","https://openalex.org/W6889955440"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2159052453","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W4297051394","https://openalex.org/W2752972570","https://openalex.org/W4386815338","https://openalex.org/W2145836866","https://openalex.org/W2803255133"],"abstract_inverted_index":{"Due":[0],"to":[1,46,92,117,138,162,180,185,191],"the":[2,5,34,47,54,72,94,110,140,155,182,196,209,216,224],"nonstationary":[3],"nature,":[4],"distribution":[6,20,30,42,74,116,143,163,190],"of":[7,144,149,157,195],"real-world":[8,205,234],"multivariate":[9],"time":[10,99],"series":[11],"(MTS)":[12],"changes":[13,164],"over":[14,37,98,215],"time,":[15],"which":[16],"is":[17],"known":[18],"as":[19,112],"drift.":[21],"Most":[22],"existing":[23],"MTS":[24,66,206,218],"forecasting":[25,35,219],"models":[26],"greatly":[27],"suffer":[28],"from":[29,58,77],"drift":[31,43],"and":[32,103,108,160,188,213,231],"degrade":[33],"performance":[36],"time.":[38],"Existing":[39],"methods":[40,69],"address":[41],"via":[44],"adapting":[45],"latest":[48],"arrived":[49],"data":[50,105],"or":[51],"self-correcting":[52],"per":[53],"meta":[55],"knowledge":[56],"derived":[57],"future":[59,104],"data.":[60],"Despite":[61],"their":[62],"great":[63],"success":[64],"in":[65,106,233],"forecasting,":[67],"these":[68],"hardly":[70],"capture":[71],"intrinsic":[73],"changes,":[75],"especially":[76],"a":[78,84,113,122,167,186],"distributional":[79,96],"perspective.":[80],"Accordingly,":[81],"we":[82,173],"propose":[83],"novel":[85,123],"framework":[86],"temporal":[87,114,124,130,150,197],"conditional":[88,115,175,198],"variational":[89],"autoencoder":[90],"(TCVAE)":[91],"model":[93],"dynamic":[95],"dependencies":[97,111],"between":[100],"historical":[101],"observations":[102],"MTSs":[107],"infer":[109],"leverage":[118],"latent":[119,145],"variables.":[120,146],"Specifically,":[121],"Hawkes":[125],"attention":[126,169],"(THA)":[127],"mechanism":[128,170],"represents":[129],"factors":[131,151],"that":[132],"subsequently":[133],"fed":[134],"into":[135],"feedforward":[136],"networks":[137],"estimate":[139],"prior":[141,183],"Gaussian":[142,184],"The":[147],"representation":[148],"further":[152,222],"dynamically":[153],"adjusts":[154],"structures":[156],"Transformer-based":[158],"encoder":[159],"decoder":[161],"by":[165],"leveraging":[166],"gated":[168],"(GAM).":[171],"Moreover,":[172],"introduce":[174],"continuous":[176],"normalization":[177],"flow":[178],"(CCNF)":[179],"transform":[181],"complex":[187],"form-free":[189],"facilitate":[192],"flexible":[193],"inference":[194],"distribution.":[199],"Extensive":[200],"experiments":[201],"conducted":[202],"on":[203],"six":[204],"datasets":[207],"demonstrate":[208],"TCVAE's":[210],"superior":[211],"robustness":[212],"effectiveness":[214],"state-of-the-art":[217],"baselines.":[220],"We":[221],"illustrate":[223],"TCVAE":[225],"applicability":[226],"through":[227],"multifaceted":[228],"case":[229],"studies":[230],"visualization":[232],"scenarios.":[235]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1}],"updated_date":"2025-12-26T23:08:49.675405","created_date":"2025-10-10T00:00:00"}