{"id":"https://openalex.org/W4411358931","doi":"https://doi.org/10.1109/tnnls.2025.3571039","title":"Variational Hierarchical N-BEATS Model for Long-Term Time-Series Forecasting","display_name":"Variational Hierarchical N-BEATS Model for Long-Term Time-Series Forecasting","publication_year":2025,"publication_date":"2025-06-17","ids":{"openalex":"https://openalex.org/W4411358931","doi":"https://doi.org/10.1109/tnnls.2025.3571039","pmid":"https://pubmed.ncbi.nlm.nih.gov/40526553"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2025.3571039","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2025.3571039","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/A5004381296","display_name":"Raina Yang","orcid":"https://orcid.org/0000-0003-4891-7478"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Runze Yang","raw_affiliation_strings":["Department of Automation, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-4891-7478","affiliations":[{"raw_affiliation_string":"Department of Automation, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":null,"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":["School of Computing, Macquarie University, Sydney, NSW, Australia"],"raw_orcid":"https://orcid.org/0000-0003-1562-9429","affiliations":[{"raw_affiliation_string":"School of Computing, Macquarie University, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I99043593"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101967607","display_name":"Jianxun Li","orcid":"https://orcid.org/0000-0003-4205-8561"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianxun Li","raw_affiliation_strings":["Department of Automation, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-4205-8561","affiliations":[{"raw_affiliation_string":"Department of Automation, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100404947","display_name":"Jie Yang","orcid":"https://orcid.org/0000-0003-4801-7162"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Yang","raw_affiliation_strings":["Department of Automation, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-4801-7162","affiliations":[{"raw_affiliation_string":"Department of Automation, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.5421,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.83528126,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"36","issue":"10","first_page":"19398","last_page":"19410"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.7512000203132629,"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"}},"topics":[{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.7512000203132629,"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"}},{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.7336999773979187,"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/term","display_name":"Term (time)","score":0.703750491142273},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5751276016235352},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.45999985933303833},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4136672616004944},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.38719671964645386},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.37697428464889526},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.37639299035072327},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.284211128950119},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.11647975444793701},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.06260919570922852}],"concepts":[{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.703750491142273},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5751276016235352},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.45999985933303833},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4136672616004944},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.38719671964645386},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.37697428464889526},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.37639299035072327},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.284211128950119},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.11647975444793701},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.06260919570922852},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2025.3571039","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2025.3571039","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:40526553","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40526553","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":[{"score":0.5600000023841858,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"awards":[{"id":"https://openalex.org/G5623680443","display_name":null,"funder_award_id":"62376153","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6377830548","display_name":null,"funder_award_id":"DP240102050","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"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2064675550","https://openalex.org/W2980994438","https://openalex.org/W3111411606","https://openalex.org/W3138758700","https://openalex.org/W3163905744","https://openalex.org/W3177318507","https://openalex.org/W4210360375","https://openalex.org/W4311415873","https://openalex.org/W4313000399","https://openalex.org/W4382203079","https://openalex.org/W4382239356","https://openalex.org/W4382239425","https://openalex.org/W4385245566","https://openalex.org/W4385338584","https://openalex.org/W4387415039","https://openalex.org/W4392452799","https://openalex.org/W4393253042"],"related_works":["https://openalex.org/W2980611886","https://openalex.org/W42295635","https://openalex.org/W1973996291","https://openalex.org/W1919101720","https://openalex.org/W2330575325","https://openalex.org/W2163803519","https://openalex.org/W2119012848","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660"],"abstract_inverted_index":{"Long-term":[0],"time-series":[1],"forecasting":[2],"(LTSF)":[3],"is":[4],"gaining":[5],"increasing":[6],"attention":[7],"due":[8],"to":[9,38,69,92],"its":[10],"significant":[11],"challenges":[12,72],"and":[13,52,84,96,154],"real-world":[14,128],"applications.":[15],"However,":[16],"existing":[17],"studies":[18],"underexplore":[19],"the":[20,39,66,71,80,85,101,117,140],"role":[21],"of":[22,41,77],"hierarchical":[23,47,62,81,94,141],"timestamp":[24,82,142],"information":[25,31],"in":[26,106],"LTSF.":[27,135],"We":[28,136],"find":[29],"this":[30],"crucial,":[32],"as":[33,50,151],"neglecting":[34],"it":[35],"may":[36],"lead":[37],"loss":[40],"broader":[42],"perspectives":[43],"necessary":[44],"for":[45,134,156],"understanding":[46],"effects,":[48],"such":[49,150],"weekly":[51],"yearly":[53],"patterns.":[54],"Therefore,":[55],"we":[56],"propose":[57],"VH-NBEATS,":[58],"an":[59],"interpretable":[60],"variational":[61,112],"model":[63],"that":[64,139],"extends":[65],"N-BEATS":[67],"architecture":[68],"address":[70],"outlined":[73],"above.":[74],"VH-NBEATS":[75,109],"consists":[76],"two":[78],"blocks:":[79],"block":[83,143],"harmonic":[86],"seasonal":[87,95],"block,":[88],"which":[89],"are":[90,124],"designed":[91],"capture":[93],"trending":[97],"effects.":[98],"To":[99],"tackle":[100],"high":[102],"variability":[103],"often":[104],"observed":[105],"time":[107],"series,":[108],"incorporates":[110],"a":[111],"autoencoder":[113],"(VAE),":[114],"significantly":[115],"enhancing":[116],"standard":[118],"deterministic":[119],"approach.":[120],"The":[121],"experimental":[122],"results":[123],"evaluated":[125],"on":[126],"seven":[127],"datasets,":[129],"demonstrating":[130],"state-of-the-art":[131],"(SOTA)":[132],"performance":[133],"also":[137],"prove":[138],"can":[144],"enable":[145],"plug-and-play":[146],"with":[147],"any":[148],"methods,":[149],"PatchTST,":[152],"Informer,":[153],"DLinear,":[155],"better":[157],"performance.":[158]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
