{"id":"https://openalex.org/W2059802626","doi":"https://doi.org/10.1145/2429069.2429119","title":"A model-learner pattern for bayesian reasoning","display_name":"A model-learner pattern for bayesian reasoning","publication_year":2013,"publication_date":"2013-01-22","ids":{"openalex":"https://openalex.org/W2059802626","doi":"https://doi.org/10.1145/2429069.2429119","mag":"2059802626"},"language":"en","primary_location":{"id":"doi:10.1145/2429069.2429119","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2429069.2429119","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 40th annual ACM SIGPLAN-SIGACT symposium on Principles of programming languages","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/A5078684560","display_name":"Andrew D. Gordon","orcid":"https://orcid.org/0000-0002-5809-2484"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]},{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB","US"],"is_corresponding":true,"raw_author_name":"Andrew D. Gordon","raw_affiliation_strings":["Microsoft Research, Cambridge, United Kingdom","Microsoft Research, Cambridge, United Kingdom ("],"affiliations":[{"raw_affiliation_string":"Microsoft Research, Cambridge, United Kingdom","institution_ids":["https://openalex.org/I4210164937"]},{"raw_affiliation_string":"Microsoft Research, Cambridge, United Kingdom (","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054057089","display_name":"Mihhail Aizatulin","orcid":null},"institutions":[{"id":"https://openalex.org/I204136569","display_name":"The Open University","ror":"https://ror.org/05mzfcs16","country_code":"GB","type":"education","lineage":["https://openalex.org/I204136569"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Mihhail Aizatulin","raw_affiliation_strings":["Open University, Milton Keynes, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Open University, Milton Keynes, United Kingdom","institution_ids":["https://openalex.org/I204136569"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038036076","display_name":"Johannes Borgstr\u00f6m","orcid":"https://orcid.org/0000-0001-5990-5742"},"institutions":[{"id":"https://openalex.org/I123387679","display_name":"Uppsala University","ror":"https://ror.org/048a87296","country_code":"SE","type":"education","lineage":["https://openalex.org/I123387679"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Johannes Borgstrom","raw_affiliation_strings":["Uppsala University, Uppsala, Sweden","Uppsala University , Uppsala, Sweden"],"affiliations":[{"raw_affiliation_string":"Uppsala University, Uppsala, Sweden","institution_ids":["https://openalex.org/I123387679"]},{"raw_affiliation_string":"Uppsala University , Uppsala, Sweden","institution_ids":["https://openalex.org/I123387679"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024463465","display_name":"Guillaume Claret","orcid":null},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]},{"id":"https://openalex.org/I4210124949","display_name":"Microsoft Research (India)","ror":"https://ror.org/02w7f3w92","country_code":"IN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210124949"]}],"countries":["IN","US"],"is_corresponding":false,"raw_author_name":"Guillaume Claret","raw_affiliation_strings":["Microsoft Research, Bangalore, India","Microsoft Research, Bangalore, India#TAB#"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, Bangalore, India","institution_ids":["https://openalex.org/I4210124949"]},{"raw_affiliation_string":"Microsoft Research, Bangalore, India#TAB#","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051619646","display_name":"Thore Graepel","orcid":"https://orcid.org/0000-0003-3957-0310"},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]},{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"Thore Graepel","raw_affiliation_strings":["Microsoft Research, Cambridge, United Kingdom","Microsoft Research, Cambridge, United Kingdom ("],"affiliations":[{"raw_affiliation_string":"Microsoft Research, Cambridge, United Kingdom","institution_ids":["https://openalex.org/I4210164937"]},{"raw_affiliation_string":"Microsoft Research, Cambridge, United Kingdom (","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111937381","display_name":"Aditya V. Nori","orcid":null},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]},{"id":"https://openalex.org/I4210124949","display_name":"Microsoft Research (India)","ror":"https://ror.org/02w7f3w92","country_code":"IN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210124949"]}],"countries":["IN","US"],"is_corresponding":false,"raw_author_name":"Aditya V. Nori","raw_affiliation_strings":["Microsoft Research, Bangalore, India","Microsoft Research, Bangalore, India#TAB#"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, Bangalore, India","institution_ids":["https://openalex.org/I4210124949"]},{"raw_affiliation_string":"Microsoft Research, Bangalore, India#TAB#","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076139746","display_name":"Sriram K. Rajamani","orcid":"https://orcid.org/0000-0002-1400-7065"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]},{"id":"https://openalex.org/I4210124949","display_name":"Microsoft Research (India)","ror":"https://ror.org/02w7f3w92","country_code":"IN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210124949"]}],"countries":["IN","US"],"is_corresponding":false,"raw_author_name":"Sriram K. Rajamani","raw_affiliation_strings":["Microsoft Research, Bangalore, India","Microsoft Research, Bangalore, India#TAB#"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, Bangalore, India","institution_ids":["https://openalex.org/I4210124949"]},{"raw_affiliation_string":"Microsoft Research, Bangalore, India#TAB#","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081301440","display_name":"Claudio Russo","orcid":"https://orcid.org/0000-0003-4877-2424"},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]},{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"Claudio Russo","raw_affiliation_strings":["Microsoft Research, Cambridge, United Kingdom","Microsoft Research, Cambridge, United Kingdom ("],"affiliations":[{"raw_affiliation_string":"Microsoft Research, Cambridge, United Kingdom","institution_ids":["https://openalex.org/I4210164937"]},{"raw_affiliation_string":"Microsoft Research, Cambridge, United Kingdom (","institution_ids":["https://openalex.org/I1290206253"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5078684560"],"corresponding_institution_ids":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"],"apc_list":null,"apc_paid":null,"fwci":12.3559,"has_fulltext":false,"cited_by_count":38,"citation_normalized_percentile":{"value":0.98499285,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"403","last_page":"416"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9998000264167786,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9998000264167786,"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/T10028","display_name":"Topic Modeling","score":0.9922000169754028,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9883999824523926,"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/computer-science","display_name":"Computer science","score":0.7215575575828552},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5150010585784912},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.48894134163856506},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4872552454471588},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.4722259044647217},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.444672167301178},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4365699589252472},{"id":"https://openalex.org/keywords/graphical-model","display_name":"Graphical model","score":0.42767471075057983},{"id":"https://openalex.org/keywords/correctness","display_name":"Correctness","score":0.4210112392902374},{"id":"https://openalex.org/keywords/variable-order-bayesian-network","display_name":"Variable-order Bayesian network","score":0.4206107556819916},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.415030837059021},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.3208900988101959},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.25495654344558716}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7215575575828552},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5150010585784912},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.48894134163856506},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4872552454471588},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.4722259044647217},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.444672167301178},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4365699589252472},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.42767471075057983},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.4210112392902374},{"id":"https://openalex.org/C71983512","wikidata":"https://www.wikidata.org/wiki/Q7915687","display_name":"Variable-order Bayesian network","level":4,"score":0.4206107556819916},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.415030837059021},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.3208900988101959},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.25495654344558716}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/2429069.2429119","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2429069.2429119","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 40th annual ACM SIGPLAN-SIGACT symposium on Principles of programming languages","raw_type":"proceedings-article"},{"id":"pmh:oai:eprints.ucl.ac.uk.OAI2:10037394","is_oa":false,"landing_page_url":"http://discovery.ucl.ac.uk/10037394/","pdf_url":null,"source":{"id":"https://openalex.org/S4306400024","display_name":"UCL Discovery (University College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45129253","host_organization_name":"University College London","host_organization_lineage":["https://openalex.org/I45129253"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"     In:   (Proceedings) 40th ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages. (pp. pp. 403-416).  ASSOC COMPUTING MACHINERY (2013)     ","raw_type":"Proceedings paper"},{"id":"pmh:oai:eprints.ucl.ac.uk.OAI2:1514669","is_oa":false,"landing_page_url":"http://discovery.ucl.ac.uk/1514669/","pdf_url":null,"source":{"id":"https://openalex.org/S4306400024","display_name":"UCL Discovery (University College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45129253","host_organization_name":"University College London","host_organization_lineage":["https://openalex.org/I45129253"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"     In:    (pp. pp. 403-416).   (2013)     ","raw_type":"Proceedings paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":59,"referenced_works":["https://openalex.org/W32064870","https://openalex.org/W41007281","https://openalex.org/W156498718","https://openalex.org/W173955544","https://openalex.org/W184493040","https://openalex.org/W195465510","https://openalex.org/W238700879","https://openalex.org/W342302233","https://openalex.org/W810225453","https://openalex.org/W1515272691","https://openalex.org/W1535430927","https://openalex.org/W1561218590","https://openalex.org/W1585529040","https://openalex.org/W1603903339","https://openalex.org/W1734364899","https://openalex.org/W1779461120","https://openalex.org/W1846253165","https://openalex.org/W1880262756","https://openalex.org/W1890754682","https://openalex.org/W1976228570","https://openalex.org/W2009776842","https://openalex.org/W2024355065","https://openalex.org/W2025653905","https://openalex.org/W2033036630","https://openalex.org/W2043100293","https://openalex.org/W2050509196","https://openalex.org/W2056760934","https://openalex.org/W2098294295","https://openalex.org/W2100877271","https://openalex.org/W2117496083","https://openalex.org/W2118578267","https://openalex.org/W2135181456","https://openalex.org/W2135394066","https://openalex.org/W2138309709","https://openalex.org/W2140597298","https://openalex.org/W2140654465","https://openalex.org/W2150884987","https://openalex.org/W2153975459","https://openalex.org/W2155748644","https://openalex.org/W2159080219","https://openalex.org/W2169784622","https://openalex.org/W2169898528","https://openalex.org/W2170694982","https://openalex.org/W2203709713","https://openalex.org/W2298292997","https://openalex.org/W2561675875","https://openalex.org/W2593808420","https://openalex.org/W2626914210","https://openalex.org/W2798149936","https://openalex.org/W2912206496","https://openalex.org/W3140968660","https://openalex.org/W3145555275","https://openalex.org/W4230647180","https://openalex.org/W4285719527","https://openalex.org/W6633563192","https://openalex.org/W6661236838","https://openalex.org/W6682322604","https://openalex.org/W6826127017","https://openalex.org/W7048060829"],"related_works":["https://openalex.org/W2126934800","https://openalex.org/W3087071515","https://openalex.org/W643788828","https://openalex.org/W2999603699","https://openalex.org/W2947536360","https://openalex.org/W2968689489","https://openalex.org/W4302573481","https://openalex.org/W2505308168","https://openalex.org/W2464065341","https://openalex.org/W4283077537"],"abstract_inverted_index":{"A":[0,18,66,134],"Bayesian":[1,38,49],"model":[2,70,87,118,128,140],"is":[3,52,71,88],"based":[4,53,155],"on":[5,54,94,156],"a":[6,42,47,55,69,83,86,102,147],"pair":[7,56],"of":[8,21,57,114,132,149,171],"probability":[9],"distributions,":[10],"known":[11],"as":[12,37,124],"the":[13,61,95,111,168],"prior":[14,62],"and":[15,30,63,99,120,130,142,151,161],"sampling":[16,64,80],"distributions.":[17,65],"wide":[19],"range":[20],"fundamental":[22],"machine":[23],"learning":[24],"tasks,":[25],"including":[26,117],"regression,":[27],"classification,":[28],"clustering,":[29],"many":[31],"others,":[32],"can":[33],"all":[34],"be":[35],"seen":[36],"models.":[39],"We":[40],"propose":[41],"new":[43,173],"probabilistic":[44,58,92],"programming":[45,104,174],"abstraction,":[46],"typed":[48],"model,":[50],"which":[51],"expressions":[59],"for":[60,68,85,91,106],"sampler":[67],"an":[72,89],"algorithm":[73,90],"to":[74],"compute":[75],"synthetic":[76],"data":[77],"from":[78],"its":[79],"distribution,":[81],"while":[82],"learner":[84,153],"inference":[93],"model.":[96],"Models,":[97],"samplers,":[98],"learners":[100],"form":[101],"generic":[103,121],"pattern":[105],"model-based":[107],"inference.":[108],"They":[109],"support":[110],"uniform":[112],"expression":[113],"common":[115],"tasks":[116],"testing,":[119],"compositions":[122],"such":[123],"mixture":[125],"models,":[126],"evidence-based":[127],"averaging,":[129],"mixtures":[131],"experts.":[133],"formal":[135],"semantics":[136],"supports":[137],"reasoning":[138],"about":[139],"equivalence":[141],"implementation":[143],"correctness.":[144],"By":[145],"developing":[146],"series":[148],"examples":[150],"three":[152],"implementations":[154],"exact":[157],"inference,":[158],"factor":[159],"graphs,":[160],"Markov":[162],"chain":[163],"Monte":[164],"Carlo,":[165],"we":[166],"demonstrate":[167],"broad":[169],"applicability":[170],"this":[172],"pattern.":[175]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":6},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":10},{"year":2013,"cited_by_count":7}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
