{"id":"https://openalex.org/W3090043041","doi":"https://doi.org/10.1137/20m1371026","title":"High-Dimensional Gaussian Sampling: A Review and a Unifying Approach Based on a Stochastic Proximal Point Algorithm","display_name":"High-Dimensional Gaussian Sampling: A Review and a Unifying Approach Based on a Stochastic Proximal Point Algorithm","publication_year":2022,"publication_date":"2022-02-01","ids":{"openalex":"https://openalex.org/W3090043041","doi":"https://doi.org/10.1137/20m1371026","mag":"3090043041"},"language":"en","primary_location":{"id":"doi:10.1137/20m1371026","is_oa":false,"landing_page_url":"https://doi.org/10.1137/20m1371026","pdf_url":null,"source":{"id":"https://openalex.org/S160107561","display_name":"SIAM Review","issn_l":"0036-1445","issn":["0036-1445","1095-7200"],"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 Review","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2010.01510","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5042939234","display_name":"Maxime Vono","orcid":"https://orcid.org/0000-0003-4859-965X"},"institutions":[{"id":"https://openalex.org/I4210123571","display_name":"Huawei Technologies (France)","ror":"https://ror.org/02rbzf697","country_code":"FR","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210123571"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Maxime Vono","raw_affiliation_strings":["Huawei Technologies France","Signal et Communications"],"raw_orcid":"https://orcid.org/0000-0003-4859-965X","affiliations":[{"raw_affiliation_string":"Huawei Technologies France","institution_ids":["https://openalex.org/I4210123571"]},{"raw_affiliation_string":"Signal et Communications","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024149247","display_name":"Nicolas Dobigeon","orcid":"https://orcid.org/0000-0001-8127-350X"},"institutions":[{"id":"https://openalex.org/I185839726","display_name":"Institut Universitaire de France","ror":"https://ror.org/055khg266","country_code":"FR","type":"education","lineage":["https://openalex.org/I185839726"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Nicolas Dobigeon","raw_affiliation_strings":["Institut Universitaire de France","Signal et Communications"],"raw_orcid":"https://orcid.org/0000-0001-8127-350X","affiliations":[{"raw_affiliation_string":"Institut Universitaire de France","institution_ids":["https://openalex.org/I185839726"]},{"raw_affiliation_string":"Signal et Communications","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088402344","display_name":"Pierre Chainais","orcid":"https://orcid.org/0000-0003-4377-7584"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pierre Chainais","raw_affiliation_strings":["Centre de Recherche R\u00e9seau Image SysT\u00e8me Architecture et MuLtim\u00e9dia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Centre de Recherche R\u00e9seau Image SysT\u00e8me Architecture et MuLtim\u00e9dia","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.7965,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.91255539,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"64","issue":"1","first_page":"3","last_page":"56"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9993000030517578,"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"}},"topics":[{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9993000030517578,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9987000226974487,"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/gaussian","display_name":"Gaussian","score":0.6992696523666382},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5940755009651184},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.581739604473114},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5618079304695129},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.46950244903564453},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4140962064266205},{"id":"https://openalex.org/keywords/importance-sampling","display_name":"Importance sampling","score":0.4107682704925537},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3459949195384979},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13687461614608765},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10032284259796143},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.07480618357658386},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.061213552951812744}],"concepts":[{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.6992696523666382},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5940755009651184},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.581739604473114},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5618079304695129},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.46950244903564453},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4140962064266205},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.4107682704925537},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3459949195384979},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13687461614608765},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10032284259796143},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.07480618357658386},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.061213552951812744},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1137/20m1371026","is_oa":false,"landing_page_url":"https://doi.org/10.1137/20m1371026","pdf_url":null,"source":{"id":"https://openalex.org/S160107561","display_name":"SIAM Review","issn_l":"0036-1445","issn":["0036-1445","1095-7200"],"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 Review","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2010.01510","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2010.01510","pdf_url":"https://arxiv.org/pdf/2010.01510","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"text"},{"id":"pmh:oai:HAL:hal-03319153v1","is_oa":true,"landing_page_url":"https://hal.science/hal-03319153","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"https://www.siam.org/","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:lilloa.univ-lille.fr:20.500.12210/59040","is_oa":true,"landing_page_url":"http://hdl.handle.net/20.500.12210/59040","pdf_url":null,"source":{"id":"https://openalex.org/S4306402203","display_name":"LillOA (Universit\u00e9 de Lille (University Of Lille))","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210123514","host_organization_name":"Centre d'Etudes en Civilisations, Langues et Litt\u00e9ratures Etrang\u00e8res","host_organization_lineage":["https://openalex.org/I4210123514"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2010.01510","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2010.01510","pdf_url":"https://arxiv.org/pdf/2010.01510","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1938070154","display_name":"Artificial and Natural Intelligence Toulouse Institute","funder_award_id":"ANR-19-P3IA-0004","funder_id":"https://openalex.org/F4320320883","funder_display_name":"Agence Nationale de la Recherche"},{"id":"https://openalex.org/G4890478204","display_name":"Fast inference with controlled uncertainty: application to astrophysical observations.","funder_award_id":"ANR-20-CHIA-0031","funder_id":"https://openalex.org/F4320320883","funder_display_name":"Agence Nationale de la Recherche"},{"id":"https://openalex.org/G602161992","display_name":null,"funder_award_id":"ANR-19-PI3A-0004","funder_id":"https://openalex.org/F4320320883","funder_display_name":"Agence Nationale de la Recherche"},{"id":"https://openalex.org/G7225929873","display_name":"ULNE","funder_award_id":"ANR-16-IDEX-0004","funder_id":"https://openalex.org/F4320320883","funder_display_name":"Agence Nationale de la Recherche"},{"id":"https://openalex.org/G8429337512","display_name":null,"funder_award_id":"ANR-16-IDEX0004 ULNE","funder_id":"https://openalex.org/F4320320883","funder_display_name":"Agence Nationale de la Recherche"}],"funders":[{"id":"https://openalex.org/F4320320883","display_name":"Agence Nationale de la Recherche","ror":"https://ror.org/00rbzpz17"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":113,"referenced_works":["https://openalex.org/W66875960","https://openalex.org/W101682403","https://openalex.org/W192616667","https://openalex.org/W205960364","https://openalex.org/W231669596","https://openalex.org/W749681720","https://openalex.org/W1503841242","https://openalex.org/W1506342804","https://openalex.org/W1520053542","https://openalex.org/W1546004968","https://openalex.org/W1561428091","https://openalex.org/W1607751291","https://openalex.org/W1651266332","https://openalex.org/W1663973292","https://openalex.org/W1746819321","https://openalex.org/W1804464592","https://openalex.org/W1857411792","https://openalex.org/W1953936588","https://openalex.org/W1961600109","https://openalex.org/W1964310563","https://openalex.org/W1977671418","https://openalex.org/W1979926788","https://openalex.org/W1981112674","https://openalex.org/W1982652137","https://openalex.org/W1983452151","https://openalex.org/W1985093013","https://openalex.org/W1994683528","https://openalex.org/W1996977322","https://openalex.org/W1997454815","https://openalex.org/W1999759467","https://openalex.org/W2001074797","https://openalex.org/W2002418905","https://openalex.org/W2005697295","https://openalex.org/W2006681603","https://openalex.org/W2015539995","https://openalex.org/W2016910236","https://openalex.org/W2017769677","https://openalex.org/W2018158121","https://openalex.org/W2020999234","https://openalex.org/W2022217247","https://openalex.org/W2027077248","https://openalex.org/W2038497950","https://openalex.org/W2039107536","https://openalex.org/W2042261731","https://openalex.org/W2043099482","https://openalex.org/W2045079045","https://openalex.org/W2045557136","https://openalex.org/W2045656233","https://openalex.org/W2059448777","https://openalex.org/W2059998776","https://openalex.org/W2069650072","https://openalex.org/W2069739265","https://openalex.org/W2072396164","https://openalex.org/W2077195032","https://openalex.org/W2079026635","https://openalex.org/W2079559649","https://openalex.org/W2084813411","https://openalex.org/W2085803676","https://openalex.org/W2092663520","https://openalex.org/W2095018839","https://openalex.org/W2095067466","https://openalex.org/W2095775020","https://openalex.org/W2099878672","https://openalex.org/W2100705753","https://openalex.org/W2101517901","https://openalex.org/W2103133389","https://openalex.org/W2106706098","https://openalex.org/W2112796928","https://openalex.org/W2114593990","https://openalex.org/W2115755118","https://openalex.org/W2118372445","https://openalex.org/W2121947440","https://openalex.org/W2123031198","https://openalex.org/W2124704116","https://openalex.org/W2128428741","https://openalex.org/W2133840092","https://openalex.org/W2138249740","https://openalex.org/W2140207570","https://openalex.org/W2143022286","https://openalex.org/W2143266849","https://openalex.org/W2164278908","https://openalex.org/W2165363188","https://openalex.org/W2167433878","https://openalex.org/W2167943787","https://openalex.org/W2169484481","https://openalex.org/W2169485677","https://openalex.org/W2177422054","https://openalex.org/W2229551134","https://openalex.org/W2244987555","https://openalex.org/W2313953460","https://openalex.org/W2316564661","https://openalex.org/W2432517183","https://openalex.org/W2488903651","https://openalex.org/W2543381247","https://openalex.org/W2562250792","https://openalex.org/W2577537660","https://openalex.org/W2607685496","https://openalex.org/W2791673642","https://openalex.org/W2798247574","https://openalex.org/W2798909945","https://openalex.org/W2801010177","https://openalex.org/W2803113999","https://openalex.org/W2911782689","https://openalex.org/W2947000318","https://openalex.org/W2963647795","https://openalex.org/W2982843188","https://openalex.org/W2984965918","https://openalex.org/W3099094880","https://openalex.org/W3100031442","https://openalex.org/W3106359998","https://openalex.org/W4245082200","https://openalex.org/W4246697467","https://openalex.org/W4292363360"],"related_works":["https://openalex.org/W2038693912","https://openalex.org/W1991602789","https://openalex.org/W2140288152","https://openalex.org/W1582396021","https://openalex.org/W2963637926","https://openalex.org/W2807783496","https://openalex.org/W2051452952","https://openalex.org/W2330004501","https://openalex.org/W2017089693","https://openalex.org/W2703295919"],"abstract_inverted_index":{"Efficient":[0],"sampling":[1,144],"from":[2,40,44],"a":[3,17,97,104,118,142],"high-dimensional":[4],"Gaussian":[5,99,138],"distribution":[6],"is":[7],"an":[8],"old":[9],"but":[10],"high-stake":[11],"issue.":[12],"Vanilla":[13],"Cholesky":[14],"samplers":[15],"imply":[16],"computational":[18],"cost":[19],"and":[20,60,84,120,151],"memory":[21],"requirements":[22],"which":[23],"can":[24],"rapidly":[25],"become":[26],"prohibitive":[27],"in":[28,113,146],"high":[29,147],"dimension.":[30],"To":[31],"tackle":[32],"these":[33,63,74],"issues,":[34],"multiple":[35],"methods":[36,64],"have":[37,65],"been":[38,66],"proposed":[39,150],"different":[41],"communities":[42],"ranging":[43],"iterative":[45],"numerical":[46,154],"linear":[47],"algebra":[48],"to":[49,88,134],"Markov":[50],"chain":[51],"Monte":[52],"Carlo":[53],"(MCMC)":[54],"approaches.":[55],"Surprisingly,":[56],"no":[57],"complete":[58],"review":[59],"comparison":[61],"of":[62,91,107,123,125],"conducted.":[67],"This":[68,115],"paper":[69,95],"aims":[70],"at":[71],"reviewing":[72],"all":[73],"approaches":[75,129],"by":[76,102],"pointing":[77],"out":[78],"their":[79],"differences,":[80],"close":[81],"relations,":[82],"benefits":[83],"limitations.":[85],"In":[86],"addition":[87],"this":[89,94],"state":[90],"the":[92,108,126,136],"art,":[93],"proposes":[96],"unifying":[98,121],"simulation":[100,139],"framework":[101,116],"deriving":[103],"stochastic":[105],"counterpart":[106],"celebrated":[109],"proximal":[110],"point":[111],"algorithm":[112],"optimization.":[114],"offers":[117],"novel":[119],"revisit":[122],"most":[124],"existing":[127],"MCMC":[128],"while":[130],"extending":[131],"them.":[132],"Guidelines":[133],"choose":[135],"appropriate":[137],"method":[140],"for":[141],"given":[143],"problem":[145],"dimension":[148],"are":[149],"illustrated":[152],"with":[153],"examples.":[155]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-08-06T08:24:18.245995","created_date":"2025-10-10T00:00:00"}