{"id":"https://openalex.org/W7162078005","doi":"https://doi.org/10.48550/arxiv.2605.22507","title":"Generative Modeling by Value-Driven Transport","display_name":"Generative Modeling by Value-Driven Transport","publication_year":2026,"publication_date":"2026-05-21","ids":{"openalex":"https://openalex.org/W7162078005","doi":"https://doi.org/10.48550/arxiv.2605.22507"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.22507","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.22507","pdf_url":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.22507","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136810073","display_name":"Pablo Moreno-Mu\u00f1oz","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Moreno-Mu\u00f1oz, Pablo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136783135","display_name":"Adrian M\u00fcller","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"M\u00fcller, Adrian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5077167635","display_name":"Gergely Neu","orcid":"https://orcid.org/0000-0001-6287-3796"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Neu, Gergely","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"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":0.2750000059604645,"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":0.2750000059604645,"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/T11206","display_name":"Model Reduction and Neural Networks","score":0.07419999688863754,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10524","display_name":"Traffic control and management","score":0.055399999022483826,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.6274999976158142},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.5473999977111816},{"id":"https://openalex.org/keywords/optimal-control","display_name":"Optimal control","score":0.5325999855995178},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.5300999879837036},{"id":"https://openalex.org/keywords/translation","display_name":"Translation (biology)","score":0.5090000033378601},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.4341999888420105},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.42980000376701355},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.39989998936653137}],"concepts":[{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.6274999976158142},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5799000263214111},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5473999977111816},{"id":"https://openalex.org/C91575142","wikidata":"https://www.wikidata.org/wiki/Q1971426","display_name":"Optimal control","level":2,"score":0.5325999855995178},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5300999879837036},{"id":"https://openalex.org/C149364088","wikidata":"https://www.wikidata.org/wiki/Q185917","display_name":"Translation (biology)","level":4,"score":0.5090000033378601},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4431000053882599},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.4341999888420105},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.42980000376701355},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41260001063346863},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.39989998936653137},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.3822999894618988},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3370000123977661},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3292999863624573},{"id":"https://openalex.org/C14646407","wikidata":"https://www.wikidata.org/wiki/Q1430750","display_name":"Bellman equation","level":2,"score":0.32100000977516174},{"id":"https://openalex.org/C170131372","wikidata":"https://www.wikidata.org/wiki/Q7617811","display_name":"Stochastic control","level":3,"score":0.2994999885559082},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.26809999346733093},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.26570001244544983},{"id":"https://openalex.org/C41045048","wikidata":"https://www.wikidata.org/wiki/Q202843","display_name":"Linear programming","level":2,"score":0.2639000117778778},{"id":"https://openalex.org/C8272713","wikidata":"https://www.wikidata.org/wiki/Q176737","display_name":"Stochastic process","level":2,"score":0.2630999982357025},{"id":"https://openalex.org/C79772020","wikidata":"https://www.wikidata.org/wiki/Q5159264","display_name":"Conditional independence","level":2,"score":0.26030001044273376}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.22507","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.22507","pdf_url":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.22507","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.22507","pdf_url":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0,82,145],"propose":[1],"a":[2,10,29,150],"new":[3],"framework":[4],"for":[5,63,163],"generative":[6],"modeling":[7],"based":[8,98],"on":[9,99],"discrete-time":[11],"stochastic":[12],"control":[13,22,43,50],"formulation":[14],"of":[15,41,152],"measure":[16],"transport.":[17],"Adapting":[18],"classic":[19],"results":[20,155],"from":[21],"theory,":[23],"we":[24,56],"formulate":[25],"our":[26,147],"problem":[27],"as":[28,127],"linear":[30],"program":[31],"whose":[32],"dual":[33],"variables":[34],"correspond":[35],"to":[36,107,143],"the":[37,42,48,70,78,124],"\\emph{optimal":[38],"value":[39,67],"function}":[40],"problem,":[44],"which":[45,76,111],"directly":[46],"encodes":[47],"optimal":[49,66,80],"policy.":[51,81],"Exploiting":[52],"this":[53],"LP":[54],"formulation,":[55],"develop":[57],"an":[58],"efficient":[59],"simulation-free":[60],"primal-dual":[61],"algorithm":[62],"computing":[64],"approximately":[65],"functions":[68],"and":[69,116,118,129,160],"associated":[71],"\\emph{value-driven":[72],"transport}":[73],"(VDT)":[74],"policies":[75,87],"approximate":[77],"true":[79],"show":[83],"that":[84,156],"well-trained":[85],"VDT":[86],"enjoy":[88],"numerous":[89],"favorable":[90],"properties":[91],"in":[92,122,149],"comparison":[93],"with":[94,154],"other":[95],"state-of-the-art":[96],"methods":[97],"flows,":[100],"diffusions,":[101],"or":[102],"Schr\u00f6dinger":[103],"bridges:":[104],"they":[105],"lead":[106],"straight":[108],"transport":[109],"paths":[110],"can":[112,119],"be":[113,120],"simulated":[114],"quickly":[115],"robustly,":[117],"enhanced":[121],"all":[123,141],"same":[125],"ways":[126],"diffusion":[128],"flow-based":[130],"models":[131],"(e.g.,":[132],"conditional":[133],"generation,":[134],"classifier-free":[135],"guidance,":[136],"unpaired":[137],"data-to-data":[138],"translation":[139],"are":[140],"easy":[142],"incorporate).":[144],"evaluate":[146],"methodology":[148],"range":[151],"experiments,":[153],"indicate":[157],"strong":[158],"performance":[159],"good":[161],"potential":[162],"scalability.":[164]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-23T00:00:00"}