{"id":"https://openalex.org/W4289655486","doi":"https://doi.org/10.1109/isit50566.2022.9834628","title":"Adaptive Importance Sampling Message Passing","display_name":"Adaptive Importance Sampling Message Passing","publication_year":2022,"publication_date":"2022-06-26","ids":{"openalex":"https://openalex.org/W4289655486","doi":"https://doi.org/10.1109/isit50566.2022.9834628"},"language":"en","primary_location":{"id":"doi:10.1109/isit50566.2022.9834628","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit50566.2022.9834628","pdf_url":null,"source":{"id":"https://openalex.org/S4363604560","display_name":"2022 IEEE International Symposium on Information Theory (ISIT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Symposium on Information Theory (ISIT)","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/A5071066422","display_name":"Semih Akbayrak","orcid":null},"institutions":[{"id":"https://openalex.org/I83019370","display_name":"Eindhoven University of Technology","ror":"https://ror.org/02c2kyt77","country_code":"NL","type":"education","lineage":["https://openalex.org/I83019370"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Semih Akbayrak","raw_affiliation_strings":["Eindhoven University of Technology,Eindhoven,The Netherlands"],"affiliations":[{"raw_affiliation_string":"Eindhoven University of Technology,Eindhoven,The Netherlands","institution_ids":["https://openalex.org/I83019370"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077888111","display_name":"\u0130smai\u0307l \u015een\u00f6z","orcid":"https://orcid.org/0000-0001-7355-2138"},"institutions":[{"id":"https://openalex.org/I83019370","display_name":"Eindhoven University of Technology","ror":"https://ror.org/02c2kyt77","country_code":"NL","type":"education","lineage":["https://openalex.org/I83019370"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"\u0130smail \u015een\u00f6z","raw_affiliation_strings":["Eindhoven University of Technology,Eindhoven,The Netherlands"],"affiliations":[{"raw_affiliation_string":"Eindhoven University of Technology,Eindhoven,The Netherlands","institution_ids":["https://openalex.org/I83019370"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022330444","display_name":"Bert de Vries","orcid":"https://orcid.org/0000-0003-0839-174X"},"institutions":[{"id":"https://openalex.org/I83019370","display_name":"Eindhoven University of Technology","ror":"https://ror.org/02c2kyt77","country_code":"NL","type":"education","lineage":["https://openalex.org/I83019370"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Bert de Vries","raw_affiliation_strings":["Eindhoven University of Technology,Eindhoven,The Netherlands"],"affiliations":[{"raw_affiliation_string":"Eindhoven University of Technology,Eindhoven,The Netherlands","institution_ids":["https://openalex.org/I83019370"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5071066422"],"corresponding_institution_ids":["https://openalex.org/I83019370"],"apc_list":null,"apc_paid":null,"fwci":0.1046,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.27921768,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1199","last_page":"1204"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9983000159263611,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9983000159263611,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9980999827384949,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9979000091552734,"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/factor-graph","display_name":"Factor graph","score":0.7927799224853516},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7450094223022461},{"id":"https://openalex.org/keywords/message-passing","display_name":"Message passing","score":0.7084842324256897},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6463043689727783},{"id":"https://openalex.org/keywords/importance-sampling","display_name":"Importance sampling","score":0.5558366775512695},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.552026093006134},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.4960385262966156},{"id":"https://openalex.org/keywords/approximate-inference","display_name":"Approximate inference","score":0.4535256028175354},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.39013248682022095},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3878524601459503},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.38247454166412354},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.29871630668640137},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17319712042808533},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.12162470817565918},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.07132989168167114}],"concepts":[{"id":"https://openalex.org/C159246509","wikidata":"https://www.wikidata.org/wiki/Q5428725","display_name":"Factor graph","level":3,"score":0.7927799224853516},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7450094223022461},{"id":"https://openalex.org/C854659","wikidata":"https://www.wikidata.org/wiki/Q1859284","display_name":"Message passing","level":2,"score":0.7084842324256897},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6463043689727783},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.5558366775512695},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.552026093006134},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.4960385262966156},{"id":"https://openalex.org/C2777472644","wikidata":"https://www.wikidata.org/wiki/Q16968992","display_name":"Approximate inference","level":3,"score":0.4535256028175354},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39013248682022095},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3878524601459503},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.38247454166412354},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29871630668640137},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17319712042808533},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.12162470817565918},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.07132989168167114},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/isit50566.2022.9834628","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit50566.2022.9834628","pdf_url":null,"source":{"id":"https://openalex.org/S4363604560","display_name":"2022 IEEE International Symposium on Information Theory (ISIT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Symposium on Information Theory (ISIT)","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.tue.nl:openaire_cris_publications/43521765-6761-4409-aa09-3fa48570eafe","is_oa":false,"landing_page_url":"https://research.tue.nl/en/publications/43521765-6761-4409-aa09-3fa48570eafe","pdf_url":null,"source":{"id":"https://openalex.org/S4406922641","display_name":"TU/e Research Portal","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Akbayrak, S, \u015een\u00f6z, I & de Vries, B 2022, Adaptive Importance Sampling Message Passing. in 2022 IEEE International Symposium on Information Theory, ISIT 2022. Institute of Electrical and Electronics Engineers, pp. 1199-1204, 2022 IEEE International Symposium on Information Theory, ISIT 2022, Espoo, Finland, 26/06/22. https://doi.org/10.1109/ISIT50566.2022.9834628","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:pure.tue.nl:publications/43521765-6761-4409-aa09-3fa48570eafe","is_oa":false,"landing_page_url":"http://www.scopus.com/inward/record.url?scp=85136314011&partnerID=8YFLogxK","pdf_url":null,"source":{"id":"https://openalex.org/S4406922641","display_name":"TU/e Research Portal","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Akbayrak, S, \u015een\u00f6z, I & de Vries, B 2022, Adaptive Importance Sampling Message Passing. in 2022 IEEE International Symposium on Information Theory, ISIT 2022. Institute of Electrical and Electronics Engineers, pp. 1199-1204, 2022 IEEE International Symposium on Information Theory, ISIT 2022, Espoo, Finland, 26/06/22. https://doi.org/10.1109/ISIT50566.2022.9834628","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:tue:oai:pure.tue.nl:publications/43521765-6761-4409-aa09-3fa48570eafe","is_oa":false,"landing_page_url":"https://research.tue.nl/nl/publications/43521765-6761-4409-aa09-3fa48570eafe","pdf_url":null,"source":{"id":"https://openalex.org/S4306401843","display_name":"Data Archiving and Networked Services (DANS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1322597698","host_organization_name":"Royal Netherlands Academy of Arts and Sciences","host_organization_lineage":["https://openalex.org/I1322597698"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2022 IEEE International Symposium on Information Theory, ISIT 2022, 1199 - 1204","raw_type":"info:eu-repo/semantics/conferencepaper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1530235965","https://openalex.org/W1607198972","https://openalex.org/W1934021597","https://openalex.org/W1994616650","https://openalex.org/W2015731569","https://openalex.org/W2052963087","https://openalex.org/W2091990110","https://openalex.org/W2098613108","https://openalex.org/W2102716594","https://openalex.org/W2156358825","https://openalex.org/W2159080219","https://openalex.org/W2165693128","https://openalex.org/W2599969863","https://openalex.org/W2604395440","https://openalex.org/W2735102987","https://openalex.org/W2808446371","https://openalex.org/W2808618339","https://openalex.org/W2892924523","https://openalex.org/W2899346917","https://openalex.org/W2899947052","https://openalex.org/W2903198223","https://openalex.org/W2962994101","https://openalex.org/W2963173382","https://openalex.org/W2963977107","https://openalex.org/W2978729728","https://openalex.org/W2989666437","https://openalex.org/W3131289200","https://openalex.org/W3174262406","https://openalex.org/W4212863985","https://openalex.org/W4232464081","https://openalex.org/W4293052541","https://openalex.org/W4293874240","https://openalex.org/W6631190155","https://openalex.org/W6631886430","https://openalex.org/W6635824087","https://openalex.org/W6679529799","https://openalex.org/W6682648773","https://openalex.org/W6682671827","https://openalex.org/W6684528527","https://openalex.org/W6696727771","https://openalex.org/W6735450280","https://openalex.org/W6735905430","https://openalex.org/W6752474965","https://openalex.org/W6755581461","https://openalex.org/W6790071243"],"related_works":["https://openalex.org/W2120733084","https://openalex.org/W4301001985","https://openalex.org/W2953176410","https://openalex.org/W4301665663","https://openalex.org/W2122977448","https://openalex.org/W2124250880","https://openalex.org/W4226307048","https://openalex.org/W2215785064","https://openalex.org/W2184572253","https://openalex.org/W2978729728"],"abstract_inverted_index":{"The":[0,134],"aim":[1],"of":[2,16,46,66,113],"Probabilistic":[3],"Programming":[4],"(PP)":[5],"is":[6,30,108,137],"to":[7,37,62,96],"automate":[8],"inference":[9,18,24,141],"in":[10,25,33,41,103,147,163],"probabilistic":[11],"models.":[12],"One":[13],"efficient":[14,31],"realization":[15],"PP-based":[17],"concerns":[19],"variational":[20],"message":[21,107,131],"passing-based":[22,132],"(VMP)":[23],"a":[26,110,138],"factor":[27,51,77],"graph.":[28],"VMP":[29,67],"but":[32],"principle":[34],"only":[35],"leads":[36],"closed-form":[38],"update":[39],"rules":[40],"case":[42,104],"the":[43,64,81,105,114,160,164],"model":[44],"consists":[45],"conjugate":[47,50],"and/or":[48],"conditionally":[49],"pairs.":[52,78],"Recently,":[53],"Extended":[54],"Variational":[55],"Message":[56],"Passing":[57],"(EVMP)":[58],"has":[59],"been":[60],"proposed":[61,161],"broaden":[63],"applicability":[65],"by":[68,85,123],"importance":[69,82,127,150],"sampling-based":[70],"particle":[71],"methods":[72],"for":[73,159],"non-linear":[74],"and":[75,100,152],"non-conjugate":[76],"EVMP":[79],"automates":[80],"sampling":[83,128,151],"procedure":[84,129],"employing":[86],"forward":[87,106],"messages":[88],"as":[89],"proposal":[90],"distributions,":[91],"which":[92],"unfortunately":[93],"may":[94],"lead":[95],"inaccurate":[97],"estimation":[98],"results":[99],"numerical":[101],"instabilities":[102],"not":[109],"good":[111],"representative":[112],"unknown":[115],"correct":[116],"posterior.":[117],"This":[118],"paper":[119],"addresses":[120],"this":[121],"issue":[122],"integrating":[124],"an":[125,157],"adaptive":[126,149],"with":[130],"inference.":[133],"resulting":[135],"method":[136,162],"hyperparameter-free":[139],"approximate":[140],"engine":[142],"that":[143],"combines":[144],"recent":[145],"advances":[146],"stochastic":[148],"optimization":[153],"methods.":[154],"We":[155],"provide":[156],"implementation":[158],"Julia":[165],"package":[166],"ForneyLab.jl.":[167]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}
