{"id":"https://openalex.org/W4385283483","doi":"https://doi.org/10.1007/s10489-023-04644-y","title":"Quantifying quality of class-conditional generative models in time series domain","display_name":"Quantifying quality of class-conditional generative models in time series domain","publication_year":2023,"publication_date":"2023-07-26","ids":{"openalex":"https://openalex.org/W4385283483","doi":"https://doi.org/10.1007/s10489-023-04644-y"},"language":"en","primary_location":{"id":"doi:10.1007/s10489-023-04644-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10489-023-04644-y","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10489-023-04644-y.pdf","source":{"id":"https://openalex.org/S74726891","display_name":"Applied Intelligence","issn_l":"0924-669X","issn":["0924-669X","1573-7497"],"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":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10489-023-04644-y.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5027568373","display_name":"Alireza Koochali","orcid":"https://orcid.org/0000-0001-7370-9369"},"institutions":[{"id":"https://openalex.org/I137230718","display_name":"Ingenieurgesellschaft Auto und Verkehr (Germany)","ror":"https://ror.org/00j4h9q86","country_code":"DE","type":"company","lineage":["https://openalex.org/I137230718"]},{"id":"https://openalex.org/I153267046","display_name":"University of Kaiserslautern","ror":"https://ror.org/04zrf7b53","country_code":"DE","type":"education","lineage":["https://openalex.org/I153267046"]},{"id":"https://openalex.org/I33256026","display_name":"German Research Centre for Artificial Intelligence","ror":"https://ror.org/01ayc5b57","country_code":"DE","type":"funder","lineage":["https://openalex.org/I33256026"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Alireza Koochali","raw_affiliation_strings":["Computer Science Department, University of Kaiserslautern-Landau, Erwin-Schr\u00f6ingerstr 52, Kaiserslautern, 67663, Germany","DFKI GmbH, Trippstadterstr. 122, Kaiserslautern, 67663, Germany","IAV GmbH, Trippstadterstr. 122, Kaiserslautern, 67663, Germany"],"raw_orcid":"https://orcid.org/0000-0001-7370-9369","affiliations":[{"raw_affiliation_string":"Computer Science Department, University of Kaiserslautern-Landau, Erwin-Schr\u00f6ingerstr 52, Kaiserslautern, 67663, Germany","institution_ids":["https://openalex.org/I153267046"]},{"raw_affiliation_string":"DFKI GmbH, Trippstadterstr. 122, Kaiserslautern, 67663, Germany","institution_ids":["https://openalex.org/I33256026"]},{"raw_affiliation_string":"IAV GmbH, Trippstadterstr. 122, Kaiserslautern, 67663, Germany","institution_ids":["https://openalex.org/I137230718"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002561046","display_name":"Maria Walch","orcid":"https://orcid.org/0000-0003-3323-8253"},"institutions":[{"id":"https://openalex.org/I137230718","display_name":"Ingenieurgesellschaft Auto und Verkehr (Germany)","ror":"https://ror.org/00j4h9q86","country_code":"DE","type":"company","lineage":["https://openalex.org/I137230718"]},{"id":"https://openalex.org/I153267046","display_name":"University of Kaiserslautern","ror":"https://ror.org/04zrf7b53","country_code":"DE","type":"education","lineage":["https://openalex.org/I153267046"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Maria Walch","raw_affiliation_strings":["Computer Science Department, University of Kaiserslautern-Landau, Erwin-Schr\u00f6ingerstr 52, Kaiserslautern, 67663, Germany","IAV GmbH, Trippstadterstr. 122, Kaiserslautern, 67663, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Department, University of Kaiserslautern-Landau, Erwin-Schr\u00f6ingerstr 52, Kaiserslautern, 67663, Germany","institution_ids":["https://openalex.org/I153267046"]},{"raw_affiliation_string":"IAV GmbH, Trippstadterstr. 122, Kaiserslautern, 67663, Germany","institution_ids":["https://openalex.org/I137230718"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074485696","display_name":"Sankrutyayan Thota","orcid":null},"institutions":[{"id":"https://openalex.org/I137230718","display_name":"Ingenieurgesellschaft Auto und Verkehr (Germany)","ror":"https://ror.org/00j4h9q86","country_code":"DE","type":"company","lineage":["https://openalex.org/I137230718"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Sankrutyayan Thota","raw_affiliation_strings":["IAV GmbH, Trippstadterstr. 122, Kaiserslautern, 67663, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IAV GmbH, Trippstadterstr. 122, Kaiserslautern, 67663, Germany","institution_ids":["https://openalex.org/I137230718"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034356107","display_name":"Peter Schichtel","orcid":"https://orcid.org/0000-0002-7634-4964"},"institutions":[{"id":"https://openalex.org/I137230718","display_name":"Ingenieurgesellschaft Auto und Verkehr (Germany)","ror":"https://ror.org/00j4h9q86","country_code":"DE","type":"company","lineage":["https://openalex.org/I137230718"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Peter Schichtel","raw_affiliation_strings":["IAV GmbH, Trippstadterstr. 122, Kaiserslautern, 67663, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IAV GmbH, Trippstadterstr. 122, Kaiserslautern, 67663, Germany","institution_ids":["https://openalex.org/I137230718"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101904182","display_name":"Andreas Dengel","orcid":"https://orcid.org/0000-0002-6100-8255"},"institutions":[{"id":"https://openalex.org/I153267046","display_name":"University of Kaiserslautern","ror":"https://ror.org/04zrf7b53","country_code":"DE","type":"education","lineage":["https://openalex.org/I153267046"]},{"id":"https://openalex.org/I33256026","display_name":"German Research Centre for Artificial Intelligence","ror":"https://ror.org/01ayc5b57","country_code":"DE","type":"funder","lineage":["https://openalex.org/I33256026"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Andreas Dengel","raw_affiliation_strings":["Computer Science Department, University of Kaiserslautern-Landau, Erwin-Schr\u00f6ingerstr 52, Kaiserslautern, 67663, Germany","DFKI GmbH, Trippstadterstr. 122, Kaiserslautern, 67663, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Department, University of Kaiserslautern-Landau, Erwin-Schr\u00f6ingerstr 52, Kaiserslautern, 67663, Germany","institution_ids":["https://openalex.org/I153267046"]},{"raw_affiliation_string":"DFKI GmbH, Trippstadterstr. 122, Kaiserslautern, 67663, Germany","institution_ids":["https://openalex.org/I33256026"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058813180","display_name":"Sheraz Ahmed","orcid":"https://orcid.org/0000-0002-4239-6520"},"institutions":[{"id":"https://openalex.org/I33256026","display_name":"German Research Centre for Artificial Intelligence","ror":"https://ror.org/01ayc5b57","country_code":"DE","type":"funder","lineage":["https://openalex.org/I33256026"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Sheraz Ahmed","raw_affiliation_strings":["DFKI GmbH, Trippstadterstr. 122, Kaiserslautern, 67663, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DFKI GmbH, Trippstadterstr. 122, Kaiserslautern, 67663, Germany","institution_ids":["https://openalex.org/I33256026"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5027568373"],"corresponding_institution_ids":["https://openalex.org/I137230718","https://openalex.org/I153267046","https://openalex.org/I33256026"],"apc_list":{"value":2990,"currency":"USD","value_usd":2990},"apc_paid":{"value":2990,"currency":"USD","value_usd":2990},"fwci":1.0692,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.75445934,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"53","issue":"20","first_page":"24530","last_page":"24550"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9976000189781189,"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":0.9976000189781189,"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/T11309","display_name":"Music and Audio Processing","score":0.9872999787330627,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9736999869346619,"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/computer-science","display_name":"Computer science","score":0.8566865921020508},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.8462587594985962},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.7275130748748779},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.6851970553398132},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6525740027427673},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.6491232514381409},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6232420802116394},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5910525918006897},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5167517066001892},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5084458589553833},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.48013946413993835},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4268140494823456},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4243178963661194},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.41809841990470886},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08326536417007446}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8566865921020508},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8462587594985962},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.7275130748748779},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6851970553398132},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6525740027427673},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.6491232514381409},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6232420802116394},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5910525918006897},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5167517066001892},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5084458589553833},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.48013946413993835},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4268140494823456},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4243178963661194},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.41809841990470886},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08326536417007446},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s10489-023-04644-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10489-023-04644-y","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10489-023-04644-y.pdf","source":{"id":"https://openalex.org/S74726891","display_name":"Applied Intelligence","issn_l":"0924-669X","issn":["0924-669X","1573-7497"],"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":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s10489-023-04644-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10489-023-04644-y","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10489-023-04644-y.pdf","source":{"id":"https://openalex.org/S74726891","display_name":"Applied Intelligence","issn_l":"0924-669X","issn":["0924-669X","1573-7497"],"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":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.7099999785423279,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4385283483.pdf"},"referenced_works_count":13,"referenced_works":["https://openalex.org/W1965555277","https://openalex.org/W2146950091","https://openalex.org/W2884805522","https://openalex.org/W2963185411","https://openalex.org/W2972810968","https://openalex.org/W3083891030","https://openalex.org/W3123931583","https://openalex.org/W3167297489","https://openalex.org/W4205206005","https://openalex.org/W4213397551","https://openalex.org/W4285606869","https://openalex.org/W6600980277","https://openalex.org/W6601854141"],"related_works":["https://openalex.org/W2987280934","https://openalex.org/W2093104230","https://openalex.org/W4390874210","https://openalex.org/W4384918963","https://openalex.org/W4365211920","https://openalex.org/W2128027845","https://openalex.org/W4386184937","https://openalex.org/W3014948380","https://openalex.org/W1493875009","https://openalex.org/W2751624083"],"abstract_inverted_index":{"Abstract":[0],"Despite":[1],"recent":[2],"breakthroughs":[3],"in":[4,149,164,188],"the":[5,11,57,78,83,90,110,140,172],"domain":[6],"of":[7,13,60,92,113],"implicit":[8,62,165,185],"generative":[9,63,94,157,166,186],"models,":[10],"task":[12],"evaluating":[14],"these":[15],"models":[16,64,95,187],"remains":[17],"a":[18,178],"challenging":[19],"task.":[20],"With":[21],"no":[22],"single":[23],"metric":[24],"to":[25,88,108],"assess":[26,89,155],"overall":[27],"performance,":[28],"various":[29],"existing":[30,118],"metrics":[31,115],"only":[32],"offer":[33],"partial":[34],"information.":[35],"This":[36,54],"issue":[37],"is":[38,52],"further":[39],"compounded":[40],"for":[41,181],"unintuitive":[42],"data":[43],"types":[44],"such":[45],"as":[46],"time":[47,66,97,189],"series,":[48],"where":[49],"manual":[50],"inspection":[51],"infeasible.":[53],"deficiency":[55],"hinders":[56],"confident":[58],"application":[59],"modern":[61,184],"on":[65,96,104,122,125,130,133],"series":[67,98,190],"data.":[68,99],"To":[69],"alleviate":[70],"this":[71],"problem,":[72],"we":[73],"propose":[74],"two":[75,117],"new":[76],"metrics,":[77,144],"InceptionTime":[79,85],"Score":[80],"(ITS)":[81],"and":[82,128,147,160],"Fr\u00e9chet":[84],"Distance":[86],"(FITD),":[87],"quality":[91],"class-conditional":[93,156],"We":[100],"conduct":[101],"extensive":[102],"experiments":[103],"80":[105],"different":[106],"datasets":[107],"study":[109],"discriminative":[111],"capabilities":[112],"proposed":[114,141,173],"alongside":[116],"evaluation":[119,143,174],"metrics:":[120],"Train":[121,129],"Synthetic":[123,134],"Test":[124,132],"Real":[126,131],"(TSTR)":[127],"(TRTS).":[135],"Our":[136,168],"evaluations":[137],"reveal":[138],"that":[139,171],"assessment":[142],"i.e.,":[145],"ITS":[146],"FITD":[148],"combination":[150],"with":[151],"TSTR,":[152],"can":[153,176],"accurately":[154],"model":[158],"performance":[159],"detect":[161],"common":[162],"issues":[163],"models.":[167],"findings":[169],"suggest":[170],"framework":[175],"be":[177],"valuable":[179],"tool":[180],"confidently":[182],"applying":[183],"analysis.":[191]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}