{"id":"https://openalex.org/W2167947196","doi":"https://doi.org/10.1109/cvpr.2003.1211409","title":"Nonparametric belief propagation","display_name":"Nonparametric belief propagation","publication_year":2003,"publication_date":"2003-11-21","ids":{"openalex":"https://openalex.org/W2167947196","doi":"https://doi.org/10.1109/cvpr.2003.1211409","mag":"2167947196"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2003.1211409","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2003.1211409","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings.","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/A5076761279","display_name":"Erik B. Sudderth","orcid":"https://orcid.org/0000-0002-0595-9726"},"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":"E.B. Sudderth","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048047705","display_name":"Alexander Ihler","orcid":"https://orcid.org/0000-0002-4331-1015"},"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":"A.T. Ihler","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, USA","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074429265","display_name":"William T. Freeman","orcid":"https://orcid.org/0000-0002-2231-7995"},"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":"W.T. Freeman","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, USA","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5107833743","display_name":"Alan S. Willsky","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":false,"raw_author_name":"A.S. Willsky","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, USA","institution_ids":["https://openalex.org/I63966007"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5076761279"],"corresponding_institution_ids":["https://openalex.org/I63966007"],"apc_list":null,"apc_paid":null,"fwci":47.7542,"has_fulltext":false,"cited_by_count":421,"citation_normalized_percentile":{"value":0.99889017,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"I","last_page":"605"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9986000061035156,"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":0.9986000061035156,"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":0.9822999835014343,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9782000184059143,"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/graphical-model","display_name":"Graphical model","score":0.7361704111099243},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.6706594228744507},{"id":"https://openalex.org/keywords/belief-propagation","display_name":"Belief propagation","score":0.6283688545227051},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6077459454536438},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5738551616668701},{"id":"https://openalex.org/keywords/nonparametric-statistics","display_name":"Nonparametric statistics","score":0.5616964101791382},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5546813011169434},{"id":"https://openalex.org/keywords/approximate-inference","display_name":"Approximate inference","score":0.5046213865280151},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.47084495425224304},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4278803765773773},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4010164439678192},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3466761112213135},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3281822204589844},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3142967224121094}],"concepts":[{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.7361704111099243},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.6706594228744507},{"id":"https://openalex.org/C152948882","wikidata":"https://www.wikidata.org/wiki/Q4060686","display_name":"Belief propagation","level":3,"score":0.6283688545227051},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6077459454536438},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5738551616668701},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.5616964101791382},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5546813011169434},{"id":"https://openalex.org/C2777472644","wikidata":"https://www.wikidata.org/wiki/Q16968992","display_name":"Approximate inference","level":3,"score":0.5046213865280151},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.47084495425224304},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4278803765773773},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4010164439678192},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3466761112213135},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3281822204589844},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3142967224121094},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvpr.2003.1211409","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2003.1211409","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings.","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W1481420047","https://openalex.org/W1483307070","https://openalex.org/W1484324861","https://openalex.org/W1496034442","https://openalex.org/W1554743847","https://openalex.org/W1601941589","https://openalex.org/W1949116567","https://openalex.org/W1980452149","https://openalex.org/W1986557010","https://openalex.org/W2019599312","https://openalex.org/W2020999234","https://openalex.org/W2030536784","https://openalex.org/W2062122868","https://openalex.org/W2099867508","https://openalex.org/W2104974755","https://openalex.org/W2108190040","https://openalex.org/W2109026452","https://openalex.org/W2118020555","https://openalex.org/W2122512809","https://openalex.org/W2125663122","https://openalex.org/W2128716185","https://openalex.org/W2129905273","https://openalex.org/W2135997060","https://openalex.org/W2138056068","https://openalex.org/W2138215503","https://openalex.org/W2141218264","https://openalex.org/W2149760002","https://openalex.org/W2158122241","https://openalex.org/W2159080219","https://openalex.org/W2160988325","https://openalex.org/W2167947196","https://openalex.org/W2169415915","https://openalex.org/W2180905035","https://openalex.org/W2279566492","https://openalex.org/W2994340921","https://openalex.org/W3160881378","https://openalex.org/W4248721357","https://openalex.org/W4285719527","https://openalex.org/W4388323202","https://openalex.org/W6636079996","https://openalex.org/W6640791922","https://openalex.org/W6658078767","https://openalex.org/W6666091668","https://openalex.org/W6682450420","https://openalex.org/W6682657107"],"related_works":["https://openalex.org/W4368755698","https://openalex.org/W4297812452","https://openalex.org/W959529772","https://openalex.org/W2962950510","https://openalex.org/W2153267847","https://openalex.org/W4286382505","https://openalex.org/W2562956507","https://openalex.org/W3180766726","https://openalex.org/W1520194733","https://openalex.org/W2501500329"],"abstract_inverted_index":{"In":[0],"many":[1,70],"applications":[2],"of":[3,13,40,65,122,163],"graphical":[4,67,141],"models":[5,68,142],"arising":[6],"in":[7,154],"computer":[8],"vision,":[9],"the":[10,36,62,66,110,135,147],"hidden":[11],"variables":[12,38],"interest":[14],"are":[15],"most":[16],"naturally":[17],"specified":[18],"by":[19],"continuous,":[20],"non-Gaussian":[21],"distributions.":[22],"There":[23],"exist":[24],"inference":[25,43],"algorithms":[26],"for":[27,35],"discrete":[28,42],"approximations":[29,108],"to":[30,60,94,105,109,134,150],"these":[31],"continuous":[32,112],"distributions,":[33],"but":[34],"high-dimensional":[37],"typically":[39],"interest,":[41],"becomes":[44],"infeasible.":[45],"Stochastic":[46],"methods":[47,133],"such":[48],"as":[49],"particle":[50,78,131],"filters":[51,79],"provide":[52],"an":[53,101,118],"appealing":[54],"alternative.":[55],"However,":[56],"existing":[57],"techniques":[58],"fail":[59],"exploit":[61],"rich":[63],"structure":[64],"describing":[69],"vision":[71,138],"problems.":[72],"Drawing":[73],"on":[74],"ideas":[75],"from":[76],"regularized":[77],"and":[80,161],"belief":[81,89],"propagation":[82,90],"(BP),":[83],"this":[84],"paper":[85],"develops":[86],"a":[87,155],"nonparametric":[88,126],"(NBP)":[91],"algorithm":[92,115,149],"applicable":[93],"general":[95,137],"graphs.":[96],"Each":[97],"NBP":[98,129,148],"iteration":[99],"uses":[100],"efficient":[102],"sampling":[103],"procedure":[104],"update":[106],"kernel-based":[107],"true,":[111],"likelihoods.":[113],"The":[114],"can":[116,143],"accommodate":[117],"extremely":[119],"broad":[120],"class":[121],"potential":[123],"functions,":[124],"including":[125],"representations.":[127],"Thus,":[128],"extends":[130],"filtering":[132],"more":[136],"problems":[139],"that":[140],"describe.":[144],"We":[145],"apply":[146],"infer":[151],"component":[152],"interrelationships":[153],"parts-based":[156],"face":[157],"model,":[158],"allowing":[159],"location":[160],"reconstruction":[162],"occluded":[164],"features.":[165]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":8},{"year":2016,"cited_by_count":7},{"year":2015,"cited_by_count":10},{"year":2014,"cited_by_count":19},{"year":2013,"cited_by_count":20},{"year":2012,"cited_by_count":28}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}