{"id":"https://openalex.org/W3154945144","doi":"https://doi.org/10.1109/tpami.2022.3152862","title":"Deep Time Series Forecasting With Shape and Temporal Criteria","display_name":"Deep Time Series Forecasting With Shape and Temporal Criteria","publication_year":2022,"publication_date":"2022-02-24","ids":{"openalex":"https://openalex.org/W3154945144","doi":"https://doi.org/10.1109/tpami.2022.3152862","mag":"3154945144","pmid":"https://pubmed.ncbi.nlm.nih.gov/35201980"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2022.3152862","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2022.3152862","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2104.04610","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101723357","display_name":"Vincent Le Guen","orcid":"https://orcid.org/0000-0002-9889-7017"},"institutions":[{"id":"https://openalex.org/I4210096782","display_name":"Laboratoire Pluridisciplinaire de Recherche en Ing\u00e9nierie des Syst\u00e8mes, M\u00e9canique et Energ\u00e9tique","ror":"https://ror.org/00sbth994","country_code":"FR","type":"facility","lineage":["https://openalex.org/I12449238","https://openalex.org/I4210096782","https://openalex.org/I4210143826"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Vincent Le Guen","raw_affiliation_strings":["EDF Recherche et Developpement Site de Chatou, PRISME, Chatou, France"],"raw_orcid":"https://orcid.org/0000-0002-9889-7017","affiliations":[{"raw_affiliation_string":"EDF Recherche et Developpement Site de Chatou, PRISME, Chatou, France","institution_ids":["https://openalex.org/I4210096782"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017490804","display_name":"Nicolas Thome","orcid":"https://orcid.org/0000-0003-4871-3045"},"institutions":[{"id":"https://openalex.org/I124158823","display_name":"Conservatoire National des Arts et M\u00e9tiers","ror":"https://ror.org/0175hh227","country_code":"FR","type":"education","lineage":["https://openalex.org/I124158823","https://openalex.org/I4210134562"]},{"id":"https://openalex.org/I4210145724","display_name":"Centre d'Etudes et De Recherche en Informatique et Communications","ror":"https://ror.org/044j5mm75","country_code":"FR","type":"facility","lineage":["https://openalex.org/I4210145724"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Nicolas Thome","raw_affiliation_strings":["Conservatoire National des Arts et Metiers, CEDRIC, Paris, France"],"raw_orcid":"https://orcid.org/0000-0003-4871-3045","affiliations":[{"raw_affiliation_string":"Conservatoire National des Arts et Metiers, CEDRIC, Paris, France","institution_ids":["https://openalex.org/I124158823","https://openalex.org/I4210145724"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101723357"],"corresponding_institution_ids":["https://openalex.org/I4210096782"],"apc_list":null,"apc_paid":null,"fwci":8.0229,"has_fulltext":false,"cited_by_count":58,"citation_normalized_percentile":{"value":0.98339591,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"45","issue":"1","first_page":"342","last_page":"355"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9998999834060669,"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":0.9998999834060669,"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":0.991100013256073,"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/T10799","display_name":"Data Visualization and Analytics","score":0.963699996471405,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/dynamic-time-warping","display_name":"Dynamic time warping","score":0.8229899406433105},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.6983391046524048},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6521034240722656},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6025682687759399},{"id":"https://openalex.org/keywords/probabilistic-forecasting","display_name":"Probabilistic forecasting","score":0.49633532762527466},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4941394627094269},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.47821399569511414},{"id":"https://openalex.org/keywords/differentiable-function","display_name":"Differentiable function","score":0.47159111499786377},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.47059547901153564},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45678433775901794},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4451954960823059},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.44082868099212646},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3259759545326233},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23963788151741028}],"concepts":[{"id":"https://openalex.org/C88516994","wikidata":"https://www.wikidata.org/wiki/Q1268863","display_name":"Dynamic time warping","level":2,"score":0.8229899406433105},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6983391046524048},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6521034240722656},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6025682687759399},{"id":"https://openalex.org/C122282355","wikidata":"https://www.wikidata.org/wiki/Q7246855","display_name":"Probabilistic forecasting","level":3,"score":0.49633532762527466},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4941394627094269},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.47821399569511414},{"id":"https://openalex.org/C202615002","wikidata":"https://www.wikidata.org/wiki/Q783507","display_name":"Differentiable function","level":2,"score":0.47159111499786377},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.47059547901153564},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45678433775901794},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4451954960823059},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.44082868099212646},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3259759545326233},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23963788151741028},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"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":4,"locations":[{"id":"doi:10.1109/tpami.2022.3152862","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2022.3152862","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:35201980","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35201980","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 pattern analysis and machine intelligence","raw_type":null},{"id":"pmh:oai:arXiv.org:2104.04610","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2104.04610","pdf_url":"https://arxiv.org/pdf/2104.04610","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"pmh:oai:HAL:hal-03588390v1","is_oa":true,"landing_page_url":"https://hal.science/hal-03588390","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022, 45 (1), pp.342-355. ⟨10.1109/TPAMI.2022.3152862⟩","raw_type":"Journal articles"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2104.04610","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2104.04610","pdf_url":"https://arxiv.org/pdf/2104.04610","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":115,"referenced_works":["https://openalex.org/W1485009520","https://openalex.org/W1959608418","https://openalex.org/W1973207880","https://openalex.org/W2008348094","https://openalex.org/W2017377889","https://openalex.org/W2036263790","https://openalex.org/W2064675550","https://openalex.org/W2115857089","https://openalex.org/W2124958607","https://openalex.org/W2130715829","https://openalex.org/W2186910770","https://openalex.org/W2296438605","https://openalex.org/W2552480641","https://openalex.org/W2586337417","https://openalex.org/W2604695176","https://openalex.org/W2604847698","https://openalex.org/W2611561672","https://openalex.org/W2613328025","https://openalex.org/W2738930091","https://openalex.org/W2751802138","https://openalex.org/W2773625660","https://openalex.org/W2787063232","https://openalex.org/W2800296055","https://openalex.org/W2889920518","https://openalex.org/W2889928394","https://openalex.org/W2921829327","https://openalex.org/W2923329249","https://openalex.org/W2937954968","https://openalex.org/W2944327260","https://openalex.org/W2945382834","https://openalex.org/W2949468773","https://openalex.org/W2950304053","https://openalex.org/W2953102581","https://openalex.org/W2954731415","https://openalex.org/W2962101532","https://openalex.org/W2963001155","https://openalex.org/W2963358464","https://openalex.org/W2963374284","https://openalex.org/W2963405869","https://openalex.org/W2963435596","https://openalex.org/W2963438456","https://openalex.org/W2963523627","https://openalex.org/W2970309699","https://openalex.org/W2970360512","https://openalex.org/W2970747624","https://openalex.org/W2970891497","https://openalex.org/W2979776030","https://openalex.org/W2980994438","https://openalex.org/W2982493538","https://openalex.org/W2990973279","https://openalex.org/W2996552856","https://openalex.org/W2997571320","https://openalex.org/W3005921148","https://openalex.org/W3006741522","https://openalex.org/W3015379812","https://openalex.org/W3024509612","https://openalex.org/W3034426027","https://openalex.org/W3036713040","https://openalex.org/W3039352388","https://openalex.org/W3092866682","https://openalex.org/W3093018222","https://openalex.org/W3094953545","https://openalex.org/W3096746890","https://openalex.org/W3097294131","https://openalex.org/W3108262631","https://openalex.org/W3122349497","https://openalex.org/W3146950576","https://openalex.org/W3177318507","https://openalex.org/W3180769366","https://openalex.org/W4230410911","https://openalex.org/W4231057675","https://openalex.org/W4241996101","https://openalex.org/W4288094782","https://openalex.org/W4289258409","https://openalex.org/W4297791576","https://openalex.org/W4308001759","https://openalex.org/W4385245566","https://openalex.org/W6640963894","https://openalex.org/W6677302653","https://openalex.org/W6683465734","https://openalex.org/W6697136110","https://openalex.org/W6729542563","https://openalex.org/W6734312481","https://openalex.org/W6739901393","https://openalex.org/W6741853729","https://openalex.org/W6745420753","https://openalex.org/W6746015598","https://openalex.org/W6746729860","https://openalex.org/W6747989175","https://openalex.org/W6748603076","https://openalex.org/W6750480569","https://openalex.org/W6752558437","https://openalex.org/W6754403922","https://openalex.org/W6754779804","https://openalex.org/W6760513793","https://openalex.org/W6761989834","https://openalex.org/W6762250955","https://openalex.org/W6763309814","https://openalex.org/W6763675009","https://openalex.org/W6764679822","https://openalex.org/W6766065261","https://openalex.org/W6766188800","https://openalex.org/W6767549592","https://openalex.org/W6767610075","https://openalex.org/W6767782324","https://openalex.org/W6769452563","https://openalex.org/W6771703261","https://openalex.org/W6773003515","https://openalex.org/W6773967291","https://openalex.org/W6774356507","https://openalex.org/W6777467691","https://openalex.org/W6779988842","https://openalex.org/W6784531488","https://openalex.org/W6784591980","https://openalex.org/W6784835917"],"related_works":["https://openalex.org/W2341338763","https://openalex.org/W2950183183","https://openalex.org/W2030799363","https://openalex.org/W2032415964","https://openalex.org/W2288425735","https://openalex.org/W2609942398","https://openalex.org/W2764033112","https://openalex.org/W4380451100","https://openalex.org/W2772616816","https://openalex.org/W4205256820"],"abstract_inverted_index":{"This":[0],"paper":[1],"addresses":[2],"the":[3,29,32,56,153,180],"problem":[4],"of":[5,28,59,75,147,182],"multi-step":[6],"time":[7,157,186,189],"series":[8,190],"forecasting":[9,22],"for":[10,112,139,143],"non-stationary":[11],"signals":[12],"that":[13,85,115],"can":[14],"present":[15],"sudden":[16],"changes.":[17],"Current":[18],"state-of-the-art":[19],"deep":[20,60],"learning":[21],"methods,":[23],"often":[24],"trained":[25],"with":[26,161],"variants":[27],"MSE,":[30],"lack":[31],"ability":[33],"to":[34,49,87],"provide":[35],"sharp":[36,148],"predictions":[37],"in":[38,55,137,188],"deterministic":[39,113],"and":[40,52,65,68,80,92,107,123,134,149,156,171,176,185],"probabilistic":[41,128],"contexts.":[42],"To":[43],"handle":[44],"these":[45,98],"challenges,":[46],"we":[47,100,130],"propose":[48],"incorporate":[50],"shape":[51,64,122,155,184],"temporal":[53,66,124],"criteria":[54],"training":[57],"objective":[58,111],"models.":[61],"We":[62],"define":[63],"similarities":[67],"dissimilarities,":[69],"based":[70],"on":[71,174],"a":[72,109,141,145,162],"smooth":[73],"relaxation":[74],"Dynamic":[76],"Time":[77,135],"Warping":[78],"(DTW)":[79],"Temporal":[81],"Distortion":[82],"Index":[83],"(TDI),":[84],"enable":[86],"build":[88],"differentiable":[89],"loss":[90],"functions":[91],"positive":[93],"semi-definite":[94],"(PSD)":[95],"kernels.":[96],"With":[97],"tools,":[99],"introduce":[101,131],"DILATE":[102],"(DIstortion":[103],"Loss":[104],"including":[105],"shApe":[106],"TimE),":[108],"new":[110],"forecasting,":[114,129],"explicitly":[116],"incorporates":[117],"two":[118],"terms":[119],"supporting":[120],"precise":[121],"change":[125],"detection.":[126],"For":[127],"STRIPE++":[132],"(Shape":[133],"diverRsIty":[136],"Probabilistic":[138],"Ecasting),":[140],"framework":[142],"providing":[144],"set":[146],"diverse":[150],"forecasts,":[151],"where":[152],"structured":[154],"diversity":[158,167],"is":[159],"enforced":[160],"determinantal":[163],"point":[164],"process":[165],"(DPP)":[166],"loss.":[168],"Extensive":[169],"experiments":[170],"ablations":[172],"studies":[173],"synthetic":[175],"real-world":[177],"datasets":[178],"confirm":[179],"benefits":[181],"leveraging":[183],"features":[187],"forecasting.":[191]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":23},{"year":2024,"cited_by_count":19},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":2}],"updated_date":"2026-05-28T09:10:13.091523","created_date":"2025-10-10T00:00:00"}