{"id":"https://openalex.org/W4401455382","doi":"https://doi.org/10.1137/23m1581546","title":"Conditional Sampling with Monotone GANs: From Generative Models to Likelihood-Free Inference","display_name":"Conditional Sampling with Monotone GANs: From Generative Models to Likelihood-Free Inference","publication_year":2024,"publication_date":"2024-08-09","ids":{"openalex":"https://openalex.org/W4401455382","doi":"https://doi.org/10.1137/23m1581546"},"language":"en","primary_location":{"id":"doi:10.1137/23m1581546","is_oa":false,"landing_page_url":"https://doi.org/10.1137/23m1581546","pdf_url":null,"source":{"id":"https://openalex.org/S2911293512","display_name":"SIAM/ASA Journal on Uncertainty Quantification","issn_l":"2166-2525","issn":["2166-2525"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM/ASA Journal on Uncertainty Quantification","raw_type":"journal-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/A5013758180","display_name":"Ricardo Baptista","orcid":"https://orcid.org/0000-0002-5955-8418"},"institutions":[{"id":"https://openalex.org/I122411786","display_name":"California Institute of Technology","ror":"https://ror.org/05dxps055","country_code":"US","type":"education","lineage":["https://openalex.org/I122411786"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ricardo Baptista","raw_affiliation_strings":["California Institute of Technology, Pasadena, CA 91106 USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"California Institute of Technology, Pasadena, CA 91106 USA","institution_ids":["https://openalex.org/I122411786"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012461935","display_name":"Bamdad Hosseini","orcid":"https://orcid.org/0000-0001-5053-6223"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bamdad Hosseini","raw_affiliation_strings":["University of Washington, Seattle, WA 98195 USA"],"raw_orcid":"https://orcid.org/0000-0001-5053-6223","affiliations":[{"raw_affiliation_string":"University of Washington, Seattle, WA 98195 USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074720524","display_name":"Nikola Kovachki","orcid":"https://orcid.org/0000-0002-3650-2972"},"institutions":[{"id":"https://openalex.org/I4210127875","display_name":"Nvidia (United States)","ror":"https://ror.org/03jdj4y14","country_code":"US","type":"company","lineage":["https://openalex.org/I4210127875"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nikola B. Kovachki","raw_affiliation_strings":["NVIDIA, Santa Clara, CA 95051 USA"],"raw_orcid":"https://orcid.org/0000-0002-3650-2972","affiliations":[{"raw_affiliation_string":"NVIDIA, Santa Clara, CA 95051 USA","institution_ids":["https://openalex.org/I4210127875"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071702167","display_name":"Youssef Marzouk","orcid":"https://orcid.org/0000-0001-8242-3290"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Youssef M. Marzouk","raw_affiliation_strings":["Massachusetts Institute of Technology, Cambridge, MA 02139 USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology, Cambridge, MA 02139 USA","institution_ids":["https://openalex.org/I63966007"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":7.2038,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.97794154,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"12","issue":"3","first_page":"868","last_page":"900"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12056","display_name":"Markov Chains and Monte Carlo Methods","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12056","display_name":"Markov Chains and Monte Carlo Methods","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9968000054359436,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6935027241706848},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5738288164138794},{"id":"https://openalex.org/keywords/monotone-polygon","display_name":"Monotone polygon","score":0.4636237621307373},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.45349204540252686},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.40375030040740967},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3668411374092102},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.33380261063575745},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32360196113586426}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6935027241706848},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5738288164138794},{"id":"https://openalex.org/C2834757","wikidata":"https://www.wikidata.org/wiki/Q4925424","display_name":"Monotone polygon","level":2,"score":0.4636237621307373},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.45349204540252686},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.40375030040740967},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3668411374092102},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.33380261063575745},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32360196113586426},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1137/23m1581546","is_oa":false,"landing_page_url":"https://doi.org/10.1137/23m1581546","pdf_url":null,"source":{"id":"https://openalex.org/S2911293512","display_name":"SIAM/ASA Journal on Uncertainty Quantification","issn_l":"2166-2525","issn":["2166-2525"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM/ASA Journal on Uncertainty Quantification","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.4699999988079071,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G2263840398","display_name":null,"funder_award_id":"DE-SC0019303","funder_id":"https://openalex.org/F4320306084","funder_display_name":"U.S. Department of Energy"},{"id":"https://openalex.org/G3060943295","display_name":null,"funder_award_id":"DMS-2208535","funder_id":"https://openalex.org/F4320337380","funder_display_name":"Division of Mathematical Sciences"},{"id":"https://openalex.org/G4789665424","display_name":null,"funder_award_id":"N00014-22-1-2790","funder_id":"https://openalex.org/F4320306078","funder_display_name":"U.S. Department of Defense"},{"id":"https://openalex.org/G7839240705","display_name":null,"funder_award_id":"DE-SC0023187","funder_id":"https://openalex.org/F4320306084","funder_display_name":"U.S. Department of Energy"},{"id":"https://openalex.org/G8834641238","display_name":null,"funder_award_id":"FA9550-20-1-0358","funder_id":"https://openalex.org/F4320333591","funder_display_name":"Multidisciplinary University Research Initiative"}],"funders":[{"id":"https://openalex.org/F4320306078","display_name":"U.S. Department of Defense","ror":"https://ror.org/0447fe631"},{"id":"https://openalex.org/F4320306084","display_name":"U.S. Department of Energy","ror":"https://ror.org/01bj3aw27"},{"id":"https://openalex.org/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"},{"id":"https://openalex.org/F4320333591","display_name":"Multidisciplinary University Research Initiative","ror":null},{"id":"https://openalex.org/F4320337380","display_name":"Division of Mathematical Sciences","ror":"https://ror.org/051fftw81"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":57,"referenced_works":["https://openalex.org/W152055444","https://openalex.org/W1522579744","https://openalex.org/W1531455566","https://openalex.org/W1970611947","https://openalex.org/W1995565517","https://openalex.org/W1996672492","https://openalex.org/W1998037613","https://openalex.org/W2013945773","https://openalex.org/W2023103251","https://openalex.org/W2027611691","https://openalex.org/W2041944459","https://openalex.org/W2042319042","https://openalex.org/W2071970553","https://openalex.org/W2074019774","https://openalex.org/W2076149679","https://openalex.org/W2128606042","https://openalex.org/W2129728672","https://openalex.org/W2136634080","https://openalex.org/W2142737094","https://openalex.org/W2149498546","https://openalex.org/W2152657433","https://openalex.org/W2169837720","https://openalex.org/W2225156818","https://openalex.org/W2328111639","https://openalex.org/W2559655401","https://openalex.org/W2569729041","https://openalex.org/W2612690371","https://openalex.org/W2612986376","https://openalex.org/W2787894218","https://openalex.org/W2953480975","https://openalex.org/W2962851448","https://openalex.org/W2963018747","https://openalex.org/W2979424018","https://openalex.org/W2979786244","https://openalex.org/W2992005611","https://openalex.org/W2999905431","https://openalex.org/W3012496101","https://openalex.org/W3031514878","https://openalex.org/W3098700198","https://openalex.org/W3099150032","https://openalex.org/W3099212336","https://openalex.org/W3099467939","https://openalex.org/W3105387130","https://openalex.org/W3105604858","https://openalex.org/W3183498204","https://openalex.org/W3215893774","https://openalex.org/W4210960245","https://openalex.org/W4212774754","https://openalex.org/W4214925787","https://openalex.org/W4220936630","https://openalex.org/W4233762729","https://openalex.org/W4253577938","https://openalex.org/W4255839052","https://openalex.org/W4298293704","https://openalex.org/W4310446950","https://openalex.org/W4313131545","https://openalex.org/W4361249119"],"related_works":["https://openalex.org/W2380075625","https://openalex.org/W2963936214","https://openalex.org/W4301895170","https://openalex.org/W2610026222","https://openalex.org/W4390718435","https://openalex.org/W2055243143","https://openalex.org/W4390549206","https://openalex.org/W2784024314","https://openalex.org/W3137171911","https://openalex.org/W1970485118"],"abstract_inverted_index":{".We":[0],"present":[1],"a":[2,26,58],"novel":[3],"framework":[4],"for":[5],"conditional":[6,35,96],"sampling":[7,36,94],"of":[8,21,95],"probability":[9,82],"measures,":[10],"using":[11],"block":[12,22,45,70],"triangular":[13,23,46,71],"transport":[14,24],"maps.":[15,72],"We":[16],"develop":[17],"the":[18,79],"theoretical":[19],"foundations":[20],"in":[25,98],"Banach":[27],"space":[28],"setting,":[29],"establishing":[30],"general":[31],"conditions":[32],"under":[33],"which":[34],"can":[37],"be":[38],"achieved":[39],"and":[40,48,84,106,110],"drawing":[41],"connections":[42],"between":[43],"monotone":[44,62],"maps":[47],"optimal":[49],"transport.":[50],"Based":[51],"on":[52],"this":[53],"theory,":[54],"we":[55],"then":[56],"introduce":[57],"computational":[59],"approach,":[60],"called":[61],"generative":[63],"adversarial":[64],"networks":[65],"(M-GANs),":[66],"to":[67],"learn":[68],"suitable":[69],"Our":[73],"algorithm":[74],"uses":[75],"only":[76],"samples":[77],"from":[78],"underlying":[80],"joint":[81],"measure":[83],"is":[85],"hence":[86],"likelihood-free.":[87],"Numerical":[88],"experiments":[89],"with":[90],"M-GAN":[91],"demonstrate":[92],"accurate":[93],"measures":[97],"synthetic":[99],"examples,":[100],"Bayesian":[101],"inverse":[102],"problems":[103],"involving":[104],"ordinary":[105],"partial":[107],"differential":[108],"equations,":[109],"probabilistic":[111],"image":[112],"inpainting.Keywordsmeasure":[113],"transportconditional":[114],"simulationlikelihood-free":[115],"inferenceoptimal":[116],"transportGANsnormalizing":[117],"flowsMSC":[118],"codes49Q2262G8662F1560B05":[119]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2026-06-16T09:24:06.705377","created_date":"2025-10-10T00:00:00"}