{"id":"https://openalex.org/W4391388021","doi":"https://doi.org/10.1145/3643035","title":"Domain Generalization in Time Series Forecasting","display_name":"Domain Generalization in Time Series Forecasting","publication_year":2024,"publication_date":"2024-01-31","ids":{"openalex":"https://openalex.org/W4391388021","doi":"https://doi.org/10.1145/3643035"},"language":"en","primary_location":{"id":"doi:10.1145/3643035","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3643035","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3643035","source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3643035","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5083739475","display_name":"Songgaojun Deng","orcid":"https://orcid.org/0000-0002-9822-9270"},"institutions":[{"id":"https://openalex.org/I887064364","display_name":"University of Amsterdam","ror":"https://ror.org/04dkp9463","country_code":"NL","type":"education","lineage":["https://openalex.org/I887064364"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Songgaojun Deng","raw_affiliation_strings":["AIRLab, University of Amsterdam, Amsterdam, The Netherlands"],"affiliations":[{"raw_affiliation_string":"AIRLab, University of Amsterdam, Amsterdam, The Netherlands","institution_ids":["https://openalex.org/I887064364"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078355434","display_name":"Olivier Sprangers","orcid":"https://orcid.org/0000-0002-0533-4574"},"institutions":[{"id":"https://openalex.org/I887064364","display_name":"University of Amsterdam","ror":"https://ror.org/04dkp9463","country_code":"NL","type":"education","lineage":["https://openalex.org/I887064364"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Olivier Sprangers","raw_affiliation_strings":["AIRLab, University of Amsterdam, Amsterdam, The Netherlands"],"affiliations":[{"raw_affiliation_string":"AIRLab, University of Amsterdam, Amsterdam, The Netherlands","institution_ids":["https://openalex.org/I887064364"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100351330","display_name":"Ming Li","orcid":"https://orcid.org/0000-0001-7430-4961"},"institutions":[{"id":"https://openalex.org/I887064364","display_name":"University of Amsterdam","ror":"https://ror.org/04dkp9463","country_code":"NL","type":"education","lineage":["https://openalex.org/I887064364"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Ming Li","raw_affiliation_strings":["AIRLab, University of Amsterdam, Amsterdam, The Netherlands"],"affiliations":[{"raw_affiliation_string":"AIRLab, University of Amsterdam, Amsterdam, The Netherlands","institution_ids":["https://openalex.org/I887064364"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090934117","display_name":"Sebastian Schelter","orcid":"https://orcid.org/0000-0003-4722-5840"},"institutions":[{"id":"https://openalex.org/I887064364","display_name":"University of Amsterdam","ror":"https://ror.org/04dkp9463","country_code":"NL","type":"education","lineage":["https://openalex.org/I887064364"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Sebastian Schelter","raw_affiliation_strings":["University of Amsterdam, Amsterdam, The Netherlands"],"affiliations":[{"raw_affiliation_string":"University of Amsterdam, Amsterdam, The Netherlands","institution_ids":["https://openalex.org/I887064364"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031439294","display_name":"Maarten de Rijke","orcid":"https://orcid.org/0000-0002-1086-0202"},"institutions":[{"id":"https://openalex.org/I887064364","display_name":"University of Amsterdam","ror":"https://ror.org/04dkp9463","country_code":"NL","type":"education","lineage":["https://openalex.org/I887064364"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Maarten de Rijke","raw_affiliation_strings":["University of Amsterdam, Amsterdam, The Netherlands"],"affiliations":[{"raw_affiliation_string":"University of Amsterdam, Amsterdam, The Netherlands","institution_ids":["https://openalex.org/I887064364"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5083739475"],"corresponding_institution_ids":["https://openalex.org/I887064364"],"apc_list":null,"apc_paid":null,"fwci":5.7608,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.95957338,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"18","issue":"5","first_page":"1","last_page":"24"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.9970999956130981,"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/T11918","display_name":"Forecasting Techniques and Applications","score":0.9970999956130981,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.9968000054359436,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9965999722480774,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.7579376697540283},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.7256423234939575},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7125120162963867},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.574470043182373},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5455403923988342},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5153712630271912},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5123528242111206},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.48284345865249634},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36858946084976196},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16986772418022156}],"concepts":[{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.7579376697540283},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.7256423234939575},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7125120162963867},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.574470043182373},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5455403923988342},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5153712630271912},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5123528242111206},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.48284345865249634},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36858946084976196},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16986772418022156},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3643035","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3643035","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3643035","source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"},{"id":"pmh:oai:dare.uva.nl:publications/afb06b96-a3d4-4874-9f93-874f5d795ab3","is_oa":true,"landing_page_url":"https://handle.uba.uva.nl/personal/pure/en/publications/domain-generalization-in-time-series-forecasting(afb06b96-a3d4-4874-9f93-874f5d795ab3).html","pdf_url":"https://pure.uva.nl/ws/files/174241098/Domain_Generalization_in_Time_Series_Forecasting.pdf","source":{"id":"https://openalex.org/S4306400088","display_name":"UvA-DARE (University of Amsterdam)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I887064364","host_organization_name":"University of Amsterdam","host_organization_lineage":["https://openalex.org/I887064364"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Deng, S, Sprangers, O, Li, M, Schelter, S & de Rijke, M 2024, 'Domain Generalization in Time Series Forecasting', ACM Transactions on Knowledge Discovery from Data, vol. 18, no. 5, 113. https://doi.org/10.1145/3643035","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"doi:10.1145/3643035","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3643035","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3643035","source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6280615682","display_name":null,"funder_award_id":"NWA.1389.20.183","funder_id":"https://openalex.org/F4320321800","funder_display_name":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek"},{"id":"https://openalex.org/G629491556","display_name":null,"funder_award_id":"(NWO)","funder_id":"https://openalex.org/F4320321800","funder_display_name":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek"}],"funders":[{"id":"https://openalex.org/F4320321799","display_name":"Ministerie van Onderwijs, Cultuur en Wetenschap","ror":"https://ror.org/02x3w5g21"},{"id":"https://openalex.org/F4320321800","display_name":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek","ror":"https://ror.org/04jsz6e67"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4391388021.pdf","grobid_xml":"https://content.openalex.org/works/W4391388021.grobid-xml"},"referenced_works_count":70,"referenced_works":["https://openalex.org/W251438302","https://openalex.org/W592244745","https://openalex.org/W605243474","https://openalex.org/W1924770834","https://openalex.org/W1965792011","https://openalex.org/W1988277750","https://openalex.org/W2012079387","https://openalex.org/W2019983814","https://openalex.org/W2064675550","https://openalex.org/W2098148222","https://openalex.org/W2133564696","https://openalex.org/W2135046866","https://openalex.org/W2161826494","https://openalex.org/W2166361350","https://openalex.org/W2416547532","https://openalex.org/W2519091744","https://openalex.org/W2525579820","https://openalex.org/W2593740144","https://openalex.org/W2606436201","https://openalex.org/W2607045400","https://openalex.org/W2766373678","https://openalex.org/W2768348081","https://openalex.org/W2768949383","https://openalex.org/W2787226294","https://openalex.org/W2792764867","https://openalex.org/W2806187986","https://openalex.org/W2811507150","https://openalex.org/W2884771968","https://openalex.org/W2889965839","https://openalex.org/W2954731415","https://openalex.org/W2970971581","https://openalex.org/W2974291863","https://openalex.org/W2980994438","https://openalex.org/W2991497298","https://openalex.org/W3022643593","https://openalex.org/W3115700835","https://openalex.org/W3124219615","https://openalex.org/W3136873846","https://openalex.org/W3159425987","https://openalex.org/W3194294871","https://openalex.org/W4206753975","https://openalex.org/W4210257598","https://openalex.org/W4213041519","https://openalex.org/W4213416527","https://openalex.org/W4221167889","https://openalex.org/W4226450359","https://openalex.org/W4230674625","https://openalex.org/W4240592325","https://openalex.org/W4246999471","https://openalex.org/W4255556797","https://openalex.org/W4287024901","https://openalex.org/W4287205383","https://openalex.org/W4287728573","https://openalex.org/W4288055550","https://openalex.org/W4288287305","https://openalex.org/W4292283308","https://openalex.org/W4295312788","https://openalex.org/W4297734170","https://openalex.org/W4297969478","https://openalex.org/W4302013494","https://openalex.org/W4385245566","https://openalex.org/W6617744952","https://openalex.org/W6637618735","https://openalex.org/W6684441963","https://openalex.org/W6739901393","https://openalex.org/W6765285020","https://openalex.org/W6776486363","https://openalex.org/W6780233385","https://openalex.org/W6794339910","https://openalex.org/W6807384801"],"related_works":["https://openalex.org/W3162204513","https://openalex.org/W2371138613","https://openalex.org/W2048963458","https://openalex.org/W43109613","https://openalex.org/W2359952343","https://openalex.org/W2239445980","https://openalex.org/W2080152487","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660"],"abstract_inverted_index":{"Domain":[0,20],"generalization":[1,21,42,79,202,227],"aims":[2],"to":[3,10,31,40,73,130,204,242],"design":[4],"models":[5,228],"that":[6,137],"can":[7,239],"effectively":[8],"generalize":[9],"unseen":[11],"target":[12],"domains":[13,92,136,152,183],"by":[14,146],"learning":[15,198],"from":[16,181],"observed":[17],"source":[18],"domains.":[19],"poses":[22],"a":[23,70,87,110],"significant":[24],"challenge":[25],"for":[26,46],"time":[27,47,81,90,117,178,244],"series":[28,48,82,91,118,179,245],"data,":[29,49],"due":[30],"varying":[32],"data":[33,66],"distributions":[34],"and":[35,64,97,153,176,188,200,224,238],"temporal":[36,62],"dependencies.":[37],"Existing":[38],"approaches":[39,203],"domain":[41,78,121,156,160,201,226],"are":[43],"not":[44],"designed":[45],"which":[50],"often":[51],"results":[52],"in":[53,80],"suboptimal":[54],"or":[55],"unstable":[56],"performance":[57,133,149],"when":[58],"confronted":[59],"with":[60,159],"diverse":[61,182],"patterns":[63],"complex":[65],"characteristics.":[67],"We":[68,84,141,164],"propose":[69,154],"novel":[71],"approach":[72],"tackle":[74],"the":[75,107,143,148,155,166,221],"problem":[76],"of":[77,109,168],"forecasting.":[83],"focus":[85],"on":[86,171],"scenario":[88],"where":[89],"share":[93],"certain":[94],"common":[95],"attributes":[96],"exhibit":[98,138],"no":[99],"abrupt":[100],"distribution":[101],"shifts.":[102],"Our":[103,190],"method":[104,170,191,215,234],"revolves":[105],"around":[106],"incorporation":[108],"key":[111],"regularization":[112,123,144,158],"term":[113,145],"into":[114,208],"an":[115],"existing":[116],"forecasting":[119],"model:":[120],"discrepancy":[122,157],".":[124,163],"In":[125,211],"this":[126],"way,":[127],"we":[128],"aim":[129],"enforce":[131],"consistent":[132],"across":[134,229],"different":[135],"distinct":[139],"patterns.":[140],"calibrate":[142],"investigating":[147],"within":[150],"individual":[151],"difficulty":[161],"awareness":[162],"demonstrate":[165],"effectiveness":[167],"our":[169,214,233],"multiple":[172],"datasets,":[173],"including":[174],"synthetic":[175],"real-world":[177],"datasets":[180],"such":[184],"as":[185],"retail,":[186],"transportation,":[187],"finance.":[189],"is":[192,235],"compared":[193],"against":[194],"traditional":[195],"methods,":[196],"deep":[197],"models,":[199],"provide":[205],"comprehensive":[206],"insights":[207],"its":[209],"performance.":[210],"these":[212],"experiments,":[213],"showcases":[216],"superior":[217],"performance,":[218],"surpassing":[219],"both":[220],"base":[222],"model":[223],"competing":[225],"all":[230],"datasets.":[231],"Furthermore,":[232],"highly":[236],"general":[237],"be":[240],"applied":[241],"various":[243],"models.":[246]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
