{"id":"https://openalex.org/W4416195245","doi":"https://doi.org/10.1145/3768292.3770391","title":"Robust time series generation via Schr\u00f6dinger Bridge: a comprehensive evaluation","display_name":"Robust time series generation via Schr\u00f6dinger Bridge: a comprehensive evaluation","publication_year":2025,"publication_date":"2025-11-14","ids":{"openalex":"https://openalex.org/W4416195245","doi":"https://doi.org/10.1145/3768292.3770391"},"language":"en","primary_location":{"id":"doi:10.1145/3768292.3770391","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3768292.3770391","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th ACM International Conference on AI in Finance","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2503.02943","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120446993","display_name":"Alexandre Alouadi","orcid":"https://orcid.org/0009-0008-2582-4328"},"institutions":[{"id":"https://openalex.org/I142476485","display_name":"\u00c9cole Polytechnique","ror":"https://ror.org/05hy3tk52","country_code":"FR","type":"education","lineage":["https://openalex.org/I142476485","https://openalex.org/I4210145102"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Alexandre Alouadi","raw_affiliation_strings":["Ecole Polytechnique, Paris, France"],"raw_orcid":"https://orcid.org/0009-0008-2582-4328","affiliations":[{"raw_affiliation_string":"Ecole Polytechnique, Paris, France","institution_ids":["https://openalex.org/I142476485"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081456435","display_name":"Baptiste Barreau","orcid":"https://orcid.org/0000-0001-9045-0141"},"institutions":[{"id":"https://openalex.org/I95549939","display_name":"BNP Paribas (France)","ror":"https://ror.org/02v616z87","country_code":"FR","type":"company","lineage":["https://openalex.org/I95549939"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Baptiste Barreau","raw_affiliation_strings":["BNP PARIBAS, Paris, France"],"raw_orcid":"https://orcid.org/0000-0001-9045-0141","affiliations":[{"raw_affiliation_string":"BNP PARIBAS, Paris, France","institution_ids":["https://openalex.org/I95549939"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005974259","display_name":"Laurent Carlier","orcid":"https://orcid.org/0009-0000-0631-6100"},"institutions":[{"id":"https://openalex.org/I95549939","display_name":"BNP Paribas (France)","ror":"https://ror.org/02v616z87","country_code":"FR","type":"company","lineage":["https://openalex.org/I95549939"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Laurent Carlier","raw_affiliation_strings":["BNP PARIBAS, Paris, France"],"raw_orcid":"https://orcid.org/0009-0000-0631-6100","affiliations":[{"raw_affiliation_string":"BNP PARIBAS, Paris, France","institution_ids":["https://openalex.org/I95549939"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101780016","display_name":"Huy\u00ean Pham","orcid":"https://orcid.org/0000-0002-9758-3550"},"institutions":[{"id":"https://openalex.org/I142476485","display_name":"\u00c9cole Polytechnique","ror":"https://ror.org/05hy3tk52","country_code":"FR","type":"education","lineage":["https://openalex.org/I142476485","https://openalex.org/I4210145102"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Huy\u00ean Pham","raw_affiliation_strings":["Ecole Polytechnique, Paris, France"],"raw_orcid":"https://orcid.org/0000-0002-9758-3550","affiliations":[{"raw_affiliation_string":"Ecole Polytechnique, Paris, France","institution_ids":["https://openalex.org/I142476485"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5120446993"],"corresponding_institution_ids":["https://openalex.org/I142476485"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.31783293,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"906","last_page":"914"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.5582000017166138,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.5582000017166138,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.16830000281333923,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.06639999896287918,"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/robustness","display_name":"Robustness (evolution)","score":0.656000018119812},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5133000016212463},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4812999963760376},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.47110000252723694},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.396699994802475},{"id":"https://openalex.org/keywords/time-horizon","display_name":"Time horizon","score":0.3456000089645386},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.31859999895095825},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.3156000077724457}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.656000018119812},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6148999929428101},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5133000016212463},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4812999963760376},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.47110000252723694},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.46869999170303345},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4260999858379364},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.396699994802475},{"id":"https://openalex.org/C28761237","wikidata":"https://www.wikidata.org/wiki/Q7805321","display_name":"Time horizon","level":2,"score":0.3456000089645386},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.31859999895095825},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.3156000077724457},{"id":"https://openalex.org/C8272713","wikidata":"https://www.wikidata.org/wiki/Q176737","display_name":"Stochastic process","level":2,"score":0.31189998984336853},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.3082999885082245},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.28600001335144043},{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.28040000796318054},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.27390000224113464},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2703000009059906},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.26420000195503235},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.26170000433921814},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.2597000002861023},{"id":"https://openalex.org/C127491075","wikidata":"https://www.wikidata.org/wiki/Q7617825","display_name":"Stochastic modelling","level":2,"score":0.25929999351501465},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.25839999318122864},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.25769999623298645},{"id":"https://openalex.org/C32230216","wikidata":"https://www.wikidata.org/wiki/Q7882499","display_name":"Uncertainty quantification","level":2,"score":0.2563000023365021}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3768292.3770391","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3768292.3770391","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th ACM International Conference on AI in Finance","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2503.02943","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2503.02943","pdf_url":"https://arxiv.org/pdf/2503.02943","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":null,"raw_type":null}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2503.02943","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2503.02943","pdf_url":"https://arxiv.org/pdf/2503.02943","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":null,"raw_type":null},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W2040731319","https://openalex.org/W2585502432","https://openalex.org/W2963170010","https://openalex.org/W3015694082","https://openalex.org/W3157027468","https://openalex.org/W4312695414","https://openalex.org/W4366958443","https://openalex.org/W4413287696"],"related_works":[],"abstract_inverted_index":{"We":[0,108],"investigate":[1],"the":[2,6,55,59,64,101,138],"generative":[3,106],"capabilities":[4],"of":[5,58,80,100],"Schr\u00f6dinger":[7],"Bridge":[8],"(SB)":[9],"approach":[10,66],"for":[11,82,148],"time":[12,18,61,86,114,149],"series.":[13,62,87],"The":[14,152],"SB":[15,65,102,139],"framework":[16],"formulates":[17],"series":[19,115,150],"synthesis":[20],"as":[21,142],"an":[22],"entropic":[23],"optimal":[24],"interpolation":[25],"transport":[26],"problem":[27],"between":[28],"a":[29,37,44,49,78,97,143],"reference":[30],"probability":[31],"measure":[32],"on":[33],"path":[34],"space":[35],"and":[36,105,125,145],"target":[38,60],"joint":[39],"distribution.":[40],"This":[41],"results":[42,133],"in":[43,71],"stochastic":[45],"differential":[46],"equation":[47],"over":[48],"finite":[50],"horizon":[51],"that":[52],"accurately":[53],"captures":[54],"temporal":[56,130],"dynamics":[57],"While":[63],"has":[67],"been":[68],"largely":[69],"explored":[70],"fields":[72],"like":[73],"image":[74],"generation,":[75],"there":[76],"is":[77,154],"scarcity":[79],"studies":[81],"its":[83,122],"application":[84],"to":[85,127],"In":[88],"this":[89,93],"work,":[90],"we":[91],"bridge":[92],"gap":[94],"by":[95],"conducting":[96],"comprehensive":[98],"evaluation":[99],"method\u2019s":[103],"robustness":[104],"performance.":[107],"benchmark":[109],"it":[110],"against":[111],"state-of-the-art":[112],"(SOTA)":[113],"generation":[116],"methods":[117],"across":[118],"diverse":[119],"datasets,":[120],"assessing":[121],"strengths,":[123],"limitations,":[124],"ability":[126],"model":[128],"complex":[129],"dependencies.":[131],"Our":[132],"offer":[134],"valuable":[135],"insights":[136],"into":[137],"framework\u2019s":[140],"potential":[141],"versatile":[144],"robust":[146],"tool":[147],"generation.":[151],"code":[153],"available":[155],"at":[156],"https://github.com/alexouadi/SBTS.":[157]},"counts_by_year":[],"updated_date":"2026-05-08T15:41:06.802602","created_date":"2025-10-10T00:00:00"}
