{"id":"https://openalex.org/W4365791115","doi":"https://doi.org/10.1007/978-3-031-30637-2_11","title":"Flow-Based End-to-End Model for\u00a0Hierarchical Time Series Forecasting via\u00a0Trainable Attentive-Reconciliation","display_name":"Flow-Based End-to-End Model for\u00a0Hierarchical Time Series Forecasting via\u00a0Trainable Attentive-Reconciliation","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4365791115","doi":"https://doi.org/10.1007/978-3-031-30637-2_11"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-031-30637-2_11","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-031-30637-2_11","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"type":"book-chapter","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/A5100437621","display_name":"Shiyu Wang","orcid":"https://orcid.org/0000-0001-7747-1028"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Shiyu Wang","raw_affiliation_strings":["Antgroup, Hangzhou, 310000, China"],"affiliations":[{"raw_affiliation_string":"Antgroup, Hangzhou, 310000, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008638415","display_name":"Yinbo Sun","orcid":"https://orcid.org/0000-0002-1836-4772"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yinbo Sun","raw_affiliation_strings":["Antgroup, Hangzhou, 310000, China"],"affiliations":[{"raw_affiliation_string":"Antgroup, Hangzhou, 310000, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100322712","display_name":"Yan Wang","orcid":"https://orcid.org/0000-0002-5344-1884"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yan Wang","raw_affiliation_strings":["Antgroup, Hangzhou, 310000, China"],"affiliations":[{"raw_affiliation_string":"Antgroup, Hangzhou, 310000, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100403505","display_name":"Fan Zhou","orcid":"https://orcid.org/0000-0002-8038-8150"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fan Zhou","raw_affiliation_strings":["Antgroup, Hangzhou, 310000, China"],"affiliations":[{"raw_affiliation_string":"Antgroup, Hangzhou, 310000, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050360700","display_name":"Lintao Ma","orcid":"https://orcid.org/0000-0002-4664-4173"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin-Tao Ma","raw_affiliation_strings":["Antgroup, Hangzhou, 310000, China"],"affiliations":[{"raw_affiliation_string":"Antgroup, Hangzhou, 310000, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101545814","display_name":"James Zhang","orcid":"https://orcid.org/0000-0002-1867-7875"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"James Zhang","raw_affiliation_strings":["Antgroup, Hangzhou, 310000, China"],"affiliations":[{"raw_affiliation_string":"Antgroup, Hangzhou, 310000, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038859429","display_name":"YangFei Zheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"YangFei Zheng","raw_affiliation_strings":["Antgroup, Hangzhou, 310000, China"],"affiliations":[{"raw_affiliation_string":"Antgroup, Hangzhou, 310000, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100437621"],"corresponding_institution_ids":[],"apc_list":{"value":5000,"currency":"EUR","value_usd":5392},"apc_paid":null,"fwci":2.5733,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.88604418,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"167","last_page":"176"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9991999864578247,"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":0.9991999864578247,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.9980999827384949,"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":0.9979000091552734,"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/computer-science","display_name":"Computer science","score":0.8280115723609924},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.6553827524185181},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5817853212356567},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5474489331245422},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.495204359292984},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.469487726688385},{"id":"https://openalex.org/keywords/end-to-end-principle","display_name":"End-to-end principle","score":0.46177423000335693},{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.4517686367034912},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4513487219810486},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39443352818489075},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38515782356262207},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3541012406349182},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08760184049606323}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8280115723609924},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.6553827524185181},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5817853212356567},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5474489331245422},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.495204359292984},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.469487726688385},{"id":"https://openalex.org/C74296488","wikidata":"https://www.wikidata.org/wiki/Q2527392","display_name":"End-to-end principle","level":2,"score":0.46177423000335693},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.4517686367034912},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4513487219810486},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39443352818489075},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38515782356262207},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3541012406349182},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08760184049606323},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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":1,"locations":[{"id":"doi:10.1007/978-3-031-30637-2_11","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-031-30637-2_11","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.4099999964237213,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2034430502","https://openalex.org/W2073210389","https://openalex.org/W2790781641","https://openalex.org/W2798629644","https://openalex.org/W2948552232","https://openalex.org/W2949366731","https://openalex.org/W3008226355","https://openalex.org/W3080971905","https://openalex.org/W3120276500","https://openalex.org/W6608922918","https://openalex.org/W6739901393"],"related_works":["https://openalex.org/W2151749779","https://openalex.org/W3179968364","https://openalex.org/W1999612375","https://openalex.org/W2938107654","https://openalex.org/W4390516098","https://openalex.org/W3008587939","https://openalex.org/W2119012848","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660"],"abstract_inverted_index":null,"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}