{"id":"https://openalex.org/W3092437753","doi":null,"title":"Exact Symbolic Inference in Probabilistic Programs via Sum-Product Representations.","display_name":"Exact Symbolic Inference in Probabilistic Programs via Sum-Product Representations.","publication_year":2020,"publication_date":"2020-10-07","ids":{"openalex":"https://openalex.org/W3092437753","mag":"3092437753"},"language":"en","primary_location":{"id":"mag:3092437753","doi":null,"is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2010.03485","pdf_url":null,"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,"listed_in":[],"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":"arXiv (Cornell University)","raw_type":null},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://export.arxiv.org/pdf/2010.03485","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5009835778","display_name":"Feras A. Saad","orcid":"https://orcid.org/0000-0002-0505-795X","observed_orcids":["https://orcid.org/0000-0002-0505-795X"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Feras A. Saad","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045127387","display_name":"Martin Rinard","orcid":"https://orcid.org/0000-0001-8095-8523","observed_orcids":["https://orcid.org/0000-0001-8095-8523"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Martin Rinard","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-8095-8523","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5068340465","display_name":"Vikash K. Mansinghka","orcid":"https://orcid.org/0000-0003-2507-0833","observed_orcids":["https://orcid.org/0000-0003-2507-0833"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vikash K. Mansinghka","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-2507-0833","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.8877000212669373,"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":0.8877000212669373,"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/T10126","display_name":"Logic, programming, and type systems","score":0.061900001019239426,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"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/T11010","display_name":"Logic, Reasoning, and Knowledge","score":0.01640000008046627,"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/probabilistic-programs","display_name":"probabilistic programs","score":0.8230000138282776},{"id":"https://openalex.org/keywords/sum-product-networks","display_name":"sum-product networks","score":0.9309999942779541},{"id":"https://openalex.org/keywords/scalability","display_name":"scalability","score":0.6019999980926514}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7758727073669434},{"id":"https://openalex.org/C39920170","wikidata":"https://www.wikidata.org/wiki/Q693083","display_name":"Soundness","level":2,"score":0.746536135673523},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6728212237358093},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.6092085838317871},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5290977954864502},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.4516136944293976},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.446225106716156},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.44319960474967957},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.41727542877197266},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23024451732635498},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1553294062614441},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.09827166795730591},{"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":"mag:3092437753","doi":null,"is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2010.03485","pdf_url":null,"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,"listed_in":[],"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":"arXiv (Cornell University)","raw_type":null}],"best_oa_location":{"id":"mag:3092437753","doi":null,"is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2010.03485","pdf_url":null,"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,"listed_in":[],"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":"arXiv (Cornell University)","raw_type":null},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":60,"referenced_works":["https://openalex.org/W114565888","https://openalex.org/W128101668","https://openalex.org/W142410360","https://openalex.org/W167351231","https://openalex.org/W184493040","https://openalex.org/W258053484","https://openalex.org/W1508165687","https://openalex.org/W1729198099","https://openalex.org/W1889548941","https://openalex.org/W1890754682","https://openalex.org/W1892397232","https://openalex.org/W1928668274","https://openalex.org/W1948169740","https://openalex.org/W1960579544","https://openalex.org/W1980452149","https://openalex.org/W1999432334","https://openalex.org/W2048025009","https://openalex.org/W2060573639","https://openalex.org/W2062818807","https://openalex.org/W2069469807","https://openalex.org/W2085550081","https://openalex.org/W2093223772","https://openalex.org/W2097246321","https://openalex.org/W2097266862","https://openalex.org/W2100960835","https://openalex.org/W2105197197","https://openalex.org/W2143143555","https://openalex.org/W2146143523","https://openalex.org/W2157928966","https://openalex.org/W2159687189","https://openalex.org/W2295266283","https://openalex.org/W2295402490","https://openalex.org/W2336416123","https://openalex.org/W2394620536","https://openalex.org/W2395654200","https://openalex.org/W2395740735","https://openalex.org/W2399803916","https://openalex.org/W2406252837","https://openalex.org/W2494200839","https://openalex.org/W2511192704","https://openalex.org/W2577537660","https://openalex.org/W2612124851","https://openalex.org/W2625045736","https://openalex.org/W2736213971","https://openalex.org/W2762833920","https://openalex.org/W2808311877","https://openalex.org/W2902895875","https://openalex.org/W2904757977","https://openalex.org/W2910209909","https://openalex.org/W2910469060","https://openalex.org/W2926374695","https://openalex.org/W2945431146","https://openalex.org/W2950141451","https://openalex.org/W2954908332","https://openalex.org/W2963368172","https://openalex.org/W2980222512","https://openalex.org/W3016582770","https://openalex.org/W3029528495","https://openalex.org/W3033339947","https://openalex.org/W3123228431"],"related_works":["https://openalex.org/W3159836140","https://openalex.org/W2494200839","https://openalex.org/W7033747285","https://openalex.org/W4394669990","https://openalex.org/W4288046178","https://openalex.org/W4319049675","https://openalex.org/W2926374695","https://openalex.org/W3033339947","https://openalex.org/W2141524150","https://openalex.org/W3026670957"],"abstract_inverted_index":{"We":[0,63,102,124],"present":[1,83,103],"the":[2,26,100,107],"Sum-Product":[3],"Probabilistic":[4],"Language":[5],"(SPPL),":[6],"a":[7,16,34,38,53,69,77,126,131,138],"new":[8,84],"system":[9,147],"that":[10,56,145],"automatically":[11,114],"delivers":[12],"exact":[13,171],"solutions":[14],"to":[15,76,150,160],"broad":[17],"range":[18],"of":[19,40,68,80,93,109,128,140,173],"probabilistic":[20,35,74],"inference":[21,112],"queries.":[22],"SPPL":[23,43,65,122,129],"symbolically":[24],"represents":[25],"full":[27],"distribution":[28],"on":[29,60,89,137],"execution":[30],"traces":[31],"specified":[32],"by":[33,113],"program":[36],"using":[37],"generalization":[39],"sum-product":[41,81],"networks.":[42],"handles":[44],"continuous":[45],"and":[46,52,90,95,111,118,134,168],"discrete":[47],"distributions,":[48],"many-to-one":[49],"numerical":[50],"transformations,":[51],"query":[54],"language":[55],"includes":[57],"general":[58],"predicates":[59],"random":[61],"variables.":[62],"formalize":[64],"in":[66,121,176],"terms":[67],"novel":[70],"translation":[71,110],"strategy":[72],"from":[73],"programs":[75],"semantic":[78],"domain":[79],"representations,":[82],"algorithms":[85],"for":[86,105,156],"exactly":[87],"conditioning":[88],"computing":[91],"probabilities":[92,172],"queries,":[94],"prove":[96],"their":[97],"soundness":[98],"under":[99],"semantics.":[101],"techniques":[104],"improving":[106],"scalability":[108],"exploiting":[115],"conditional":[116],"independences":[117],"repeated":[119],"structure":[120],"programs.":[123],"implement":[125],"prototype":[127],"with":[130],"modular":[132],"architecture":[133],"evaluate":[135],"it":[136],"suite":[139],"common":[141],"benchmarks,":[142],"which":[143],"establish":[144],"our":[146],"is":[148],"up":[149,159],"3500x":[151],"faster":[152,162],"than":[153,163],"state-of-the-art":[154,164],"systems":[155],"fairness":[157],"verification;":[158],"1000x":[161],"symbolic":[165],"algebra":[166],"techniques;":[167],"can":[169],"compute":[170],"rare":[174],"events":[175],"milliseconds.":[177]},"counts_by_year":[],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2020-10-15T00:00:00"}