{"id":"https://openalex.org/W7125946445","doi":"https://doi.org/10.1109/smc58881.2025.11342981","title":"Generating Heterogeneous Multi-dimensional Data : A Comparative Study","display_name":"Generating Heterogeneous Multi-dimensional Data : A Comparative Study","publication_year":2025,"publication_date":"2025-10-05","ids":{"openalex":"https://openalex.org/W7125946445","doi":"https://doi.org/10.1109/smc58881.2025.11342981"},"language":null,"primary_location":{"id":"doi:10.1109/smc58881.2025.11342981","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11342981","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"},"type":"article","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/A5124069599","display_name":"Corbeau Michael","orcid":null},"institutions":[{"id":"https://openalex.org/I4210119061","display_name":"Institut de Recherche en Informatique de Toulouse","ror":"https://ror.org/01rx4qw44","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I205747304","https://openalex.org/I205747304","https://openalex.org/I4210119061","https://openalex.org/I4387153255","https://openalex.org/I4405258862","https://openalex.org/I4405258862"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Corbeau Michael","raw_affiliation_strings":["Institut de Recherche en Informatique de Toulouse,Toulouse,France,31400"],"affiliations":[{"raw_affiliation_string":"Institut de Recherche en Informatique de Toulouse,Toulouse,France,31400","institution_ids":["https://openalex.org/I4210119061"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124064639","display_name":"Claeys Emmanuelle","orcid":null},"institutions":[{"id":"https://openalex.org/I4210119061","display_name":"Institut de Recherche en Informatique de Toulouse","ror":"https://ror.org/01rx4qw44","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I205747304","https://openalex.org/I205747304","https://openalex.org/I4210119061","https://openalex.org/I4387153255","https://openalex.org/I4405258862","https://openalex.org/I4405258862"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Claeys Emmanuelle","raw_affiliation_strings":["Institut de Recherche en Informatique de Toulouse,Toulouse,France,31400"],"affiliations":[{"raw_affiliation_string":"Institut de Recherche en Informatique de Toulouse,Toulouse,France,31400","institution_ids":["https://openalex.org/I4210119061"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046508456","display_name":"serrurier Mathieu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210119061","display_name":"Institut de Recherche en Informatique de Toulouse","ror":"https://ror.org/01rx4qw44","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I205747304","https://openalex.org/I205747304","https://openalex.org/I4210119061","https://openalex.org/I4387153255","https://openalex.org/I4405258862","https://openalex.org/I4405258862"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Serrurier Mathieu","raw_affiliation_strings":["Institut de Recherche en Informatique de Toulouse,Toulouse,France,31400"],"affiliations":[{"raw_affiliation_string":"Institut de Recherche en Informatique de Toulouse,Toulouse,France,31400","institution_ids":["https://openalex.org/I4210119061"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109230750","display_name":"Zarate Pascale","orcid":null},"institutions":[{"id":"https://openalex.org/I4210119061","display_name":"Institut de Recherche en Informatique de Toulouse","ror":"https://ror.org/01rx4qw44","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I205747304","https://openalex.org/I205747304","https://openalex.org/I4210119061","https://openalex.org/I4387153255","https://openalex.org/I4405258862","https://openalex.org/I4405258862"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Zarat\u00e9 Pascale","raw_affiliation_strings":["Institut de Recherche en Informatique de Toulouse,Toulouse,France,31400"],"affiliations":[{"raw_affiliation_string":"Institut de Recherche en Informatique de Toulouse,Toulouse,France,31400","institution_ids":["https://openalex.org/I4210119061"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5124069599"],"corresponding_institution_ids":["https://openalex.org/I4210119061"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.71656466,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4000","last_page":"4005"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10799","display_name":"Data Visualization and Analytics","score":0.1054999977350235,"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"}},"topics":[{"id":"https://openalex.org/T10799","display_name":"Data Visualization and Analytics","score":0.1054999977350235,"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"}},{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.10450000315904617,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.065700002014637,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.541700005531311},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.44279998540878296},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.42660000920295715},{"id":"https://openalex.org/keywords/probability-distribution","display_name":"Probability distribution","score":0.4189000129699707},{"id":"https://openalex.org/keywords/statistical-model","display_name":"Statistical model","score":0.4083000123500824},{"id":"https://openalex.org/keywords/data-quality","display_name":"Data quality","score":0.40059998631477356},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.39820000529289246},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.3831000030040741},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.351500004529953}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6980000138282776},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5526000261306763},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.541700005531311},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.44279998540878296},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.42660000920295715},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.4189000129699707},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.4083000123500824},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.40059998631477356},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.39820000529289246},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.3831000030040741},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3756999969482422},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.351500004529953},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.3416999876499176},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.3312999904155731},{"id":"https://openalex.org/C557531904","wikidata":"https://www.wikidata.org/wiki/Q897825","display_name":"Firefighting","level":2,"score":0.3280999958515167},{"id":"https://openalex.org/C43555835","wikidata":"https://www.wikidata.org/wiki/Q2300258","display_name":"Conditional probability distribution","level":2,"score":0.328000009059906},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3278999924659729},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.3262999951839447},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.30889999866485596},{"id":"https://openalex.org/C18653775","wikidata":"https://www.wikidata.org/wiki/Q1333358","display_name":"Joint probability distribution","level":2,"score":0.30660000443458557},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3061000108718872},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.29269999265670776},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.2924000024795532},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.28439998626708984},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.27570000290870667},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.2734000086784363},{"id":"https://openalex.org/C2777317252","wikidata":"https://www.wikidata.org/wiki/Q18393516","display_name":"Rare events","level":2,"score":0.2702000141143799},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.250900000333786}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc58881.2025.11342981","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11342981","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":2,"referenced_works":["https://openalex.org/W2138447111","https://openalex.org/W4206566734"],"related_works":[],"abstract_inverted_index":{"Allocation":[0],"of":[1,12,28,35,89,103,115,124,148,163,189,198,203],"personnel":[2],"and":[3,75,132,150,165,168,185],"material":[4],"resources":[5],"is":[6,31,41,119],"highly":[7,200],"sensible":[8],"in":[9,85,98],"the":[10,32,36,87,100,129,137,161,178,181,186,190,196,204,213],"case":[11],"firefighter":[13,90],"interventions.":[14,91],"This":[15],"allocation":[16,30],"relies":[17],"on":[18],"simulations":[19],"to":[20,44,52,81,128,157,212],"experiment":[21],"with":[22,173,180],"various":[23,46],"scenarios.":[24,108],"The":[25,193],"main":[26],"objective":[27],"this":[29,48,111],"global":[33],"optimization":[34],"firefighters":[37],"response.":[38],"Data":[39],"generation":[40,56,215],"then":[42],"mandotory":[43],"study":[45],"scenariosIn":[47],"study,":[49],"we":[50],"propose":[51],"compare":[53],"different":[54],"data":[55,117,159,214],"methods.":[57],"Methods":[58],"such":[59,135,170],"as":[60,136,171],"Random":[61],"Sampling,":[62],"Tabular":[63,71],"Variational":[64],"Autoencoders,":[65],"standard":[66,133],"Generative":[67,72],"Adversarial":[68,73],"Networks,":[69],"Conditional":[70],"Networks":[74],"Diffusion":[76],"Probabilistic":[77],"Models":[78],"are":[79,155],"examined":[80],"ascertain":[82],"their":[83],"efficacy":[84],"capturing":[86,99],"intricacies":[88],"Traditional":[92],"evaluation":[93,114],"metrics":[94,126,141,154],"often":[95],"fall":[96],"short":[97],"nuanced":[101],"requirements":[102],"synthetic":[104,116,191],"datasets":[105],"for":[106],"real-world":[107],"To":[109],"address":[110],"gap,":[112],"an":[113],"quality":[118],"conducted":[120],"using":[121],"a":[122,174,207],"combination":[123],"domain-specific":[125],"tailored":[127],"firefighting":[130],"domain":[131],"measures":[134],"Wasserstein":[138],"distance.":[139],"Domainspecific":[140],"include":[142],"response":[143],"time":[144],"distribution,":[145,209],"spatial-temporal":[146],"distribution":[147,184,194],"interventions,":[149],"accidents":[151],"representation.":[152],"These":[153],"designed":[156],"assess":[158],"variability,":[160],"preservation":[162],"fine":[164],"complex":[166],"correlations":[167],"anomalies":[169],"event":[172],"very":[175],"low":[176],"occurrence,":[177],"conformity":[179],"initial":[182],"statistical":[183],"operational":[187],"relevance":[188],"data.":[192],"has":[195],"particularity":[197],"being":[199],"unbalanced,":[201],"none":[202],"variables":[205],"following":[206],"Gaussian":[208],"adding":[210],"complexity":[211],"process.":[216]},"counts_by_year":[],"updated_date":"2026-01-29T23:17:01.242718","created_date":"2026-01-29T00:00:00"}