{"id":"https://openalex.org/W2807539892","doi":"https://doi.org/10.1145/3211346.3211350","title":"A design proposal for Gen: probabilistic programming with fast custom inference via code generation","display_name":"A design proposal for Gen: probabilistic programming with fast custom inference via code generation","publication_year":2018,"publication_date":"2018-06-07","ids":{"openalex":"https://openalex.org/W2807539892","doi":"https://doi.org/10.1145/3211346.3211350","mag":"2807539892"},"language":"en","primary_location":{"id":"doi:10.1145/3211346.3211350","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3211346.3211350","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3211346.3211350","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd ACM SIGPLAN International Workshop on Machine Learning and Programming Languages","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3211346.3211350","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017388818","display_name":"Marco Cusumano-Towner","orcid":null},"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":true,"raw_author_name":"Marco Cusumano-Towner","raw_affiliation_strings":["Massachusetts Institute of Technology, USA"],"affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology, USA","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068340465","display_name":"Vikash K. Mansinghka","orcid":"https://orcid.org/0000-0003-2507-0833"},"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":"Vikash K. Mansinghka","raw_affiliation_strings":["Massachusetts Institute of Technology, USA"],"affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology, USA","institution_ids":["https://openalex.org/I63966007"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5017388818"],"corresponding_institution_ids":["https://openalex.org/I63966007"],"apc_list":null,"apc_paid":null,"fwci":1.1846,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.8423852,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"16","issue":null,"first_page":"52","last_page":"57"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9994000196456909,"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":0.9994000196456909,"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/T10906","display_name":"AI-based Problem Solving and Planning","score":0.9858999848365784,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9850000143051147,"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":0.8126528263092041},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.7187014222145081},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.7047389149665833},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6602128148078918},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5140162706375122},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4735628366470337},{"id":"https://openalex.org/keywords/modeling-language","display_name":"Modeling language","score":0.4275949001312256},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4271897077560425},{"id":"https://openalex.org/keywords/implementation","display_name":"Implementation","score":0.4241946339607239},{"id":"https://openalex.org/keywords/code-generation","display_name":"Code generation","score":0.41121363639831543},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34341591596603394},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.09259006381034851}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8126528263092041},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.7187014222145081},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.7047389149665833},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6602128148078918},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5140162706375122},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4735628366470337},{"id":"https://openalex.org/C179603123","wikidata":"https://www.wikidata.org/wiki/Q1941921","display_name":"Modeling language","level":3,"score":0.4275949001312256},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4271897077560425},{"id":"https://openalex.org/C26713055","wikidata":"https://www.wikidata.org/wiki/Q245962","display_name":"Implementation","level":2,"score":0.4241946339607239},{"id":"https://openalex.org/C133162039","wikidata":"https://www.wikidata.org/wiki/Q1061077","display_name":"Code generation","level":3,"score":0.41121363639831543},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34341591596603394},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.09259006381034851},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3211346.3211350","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3211346.3211350","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3211346.3211350","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd ACM SIGPLAN International Workshop on Machine Learning and Programming Languages","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3211346.3211350","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3211346.3211350","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3211346.3211350","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd ACM SIGPLAN International Workshop on Machine Learning and Programming Languages","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1000491213","display_name":null,"funder_award_id":"NDSEG","funder_id":"https://openalex.org/F4320306132","funder_display_name":"American Society for Engineering Education"},{"id":"https://openalex.org/G2452784610","display_name":null,"funder_award_id":"FA8750-17-C-0239","funder_id":"https://openalex.org/F4320338249","funder_display_name":"Air Force Civil Engineer Center"},{"id":"https://openalex.org/G4014406470","display_name":null,"funder_award_id":"-17-C-","funder_id":"https://openalex.org/F4320306078","funder_display_name":"U.S. Department of Defense"},{"id":"https://openalex.org/G4823715754","display_name":null,"funder_award_id":"NDSEG","funder_id":"https://openalex.org/F4320306078","funder_display_name":"U.S. Department of Defense"}],"funders":[{"id":"https://openalex.org/F4320306078","display_name":"U.S. Department of Defense","ror":"https://ror.org/0447fe631"},{"id":"https://openalex.org/F4320306132","display_name":"American Society for Engineering Education","ror":"https://ror.org/03ac64295"},{"id":"https://openalex.org/F4320333566","display_name":"National Defense Science and Engineering Graduate","ror":null},{"id":"https://openalex.org/F4320338249","display_name":"Air Force Civil Engineer Center","ror":"https://ror.org/006gmme17"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2807539892.pdf","grobid_xml":"https://content.openalex.org/works/W2807539892.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W32064870","https://openalex.org/W137420995","https://openalex.org/W1844453107","https://openalex.org/W1890754682","https://openalex.org/W2045656233","https://openalex.org/W2046536636","https://openalex.org/W2098355199","https://openalex.org/W2112820511","https://openalex.org/W2129728285","https://openalex.org/W2135194391","https://openalex.org/W2147356329","https://openalex.org/W2149416046","https://openalex.org/W2158637909","https://openalex.org/W2159080219","https://openalex.org/W2185558310","https://openalex.org/W2188398310","https://openalex.org/W2295266283","https://openalex.org/W2336416123","https://openalex.org/W2471980869","https://openalex.org/W2577537660","https://openalex.org/W2596701210","https://openalex.org/W2624999081","https://openalex.org/W2799261850","https://openalex.org/W2899771611","https://openalex.org/W2921051283","https://openalex.org/W2953384591","https://openalex.org/W2963172700","https://openalex.org/W2963264829","https://openalex.org/W2963977107","https://openalex.org/W4229626860","https://openalex.org/W4248681815","https://openalex.org/W4285719527","https://openalex.org/W6713134421","https://openalex.org/W6760353796"],"related_works":["https://openalex.org/W2120447654","https://openalex.org/W2977179488","https://openalex.org/W2163814182","https://openalex.org/W2766863610","https://openalex.org/W2911612295","https://openalex.org/W4247461680","https://openalex.org/W626796362","https://openalex.org/W4245356976","https://openalex.org/W4364322486","https://openalex.org/W2997997463"],"abstract_inverted_index":{"Probabilistic":[0],"programming":[1,58],"languages":[2,38,160],"have":[3],"the":[4,94,156],"potential":[5],"to":[6,13,67],"make":[7],"probabilistic":[8,57,96,159],"modeling":[9],"and":[10,24,47,71,107,149],"inference":[11,20,48,87],"easier":[12],"use":[14],"in":[15,63,147],"practice,":[16],"but":[17],"only":[18,33,140,157],"if":[19],"is":[21,111],"sufficiently":[22,69],"fast":[23,137],"accurate":[25],"for":[26,36,55,73,80,105,120,163],"real":[27],"applications.":[28],"Thus":[29],"far,":[30],"this":[31],"has":[32],"been":[34],"possible":[35],"domain-specific":[37],"that":[39,65,109,128],"focus":[40],"on":[41,90],"a":[42,53,56,102,116,129,144],"restricted":[43],"class":[44],"of":[45,85,93,132,155],"models":[46],"algorithms.":[49],"This":[50,98],"paper":[51,99],"proposes":[52],"design":[54,104],"language":[59,77,103,119],"called":[60],"Gen,":[61,106],"embedded":[62],"Julia,":[64,148],"aims":[66],"be":[68,135],"expressive":[70,113],"performant":[72],"general-purpose":[74],"use.":[75],"The":[76],"provides":[78],"constructs":[79],"automatically":[81],"generating":[82],"optimized":[83],"implementations":[84],"custom":[86,164],"tactics":[88],"based":[89],"static":[91],"analysis":[92],"target":[95],"model.":[97],"informally":[100],"describes":[101],"shows":[108,127],"Gen":[110,133],"more":[112],"than":[114,143,152],"Stan,":[115,139],"widely":[117],"used":[118],"hierarchical":[121],"Bayesian":[122],"modeling.":[123],"A":[124],"first":[125],"benchmark":[126],"prototype":[130],"implementation":[131],"can":[134],"as":[136,138],"\u223c1.4x":[141],"slower":[142],"hand-coded":[145],"sampler":[146],"\u223c7,500x":[150],"faster":[151],"Venture,":[153],"one":[154],"other":[158],"with":[161],"support":[162],"inference.":[165]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":2}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}