{"id":"https://openalex.org/W2070797946","doi":"https://doi.org/10.1109/cvpr.2011.5995724","title":"Learning message-passing inference machines for structured prediction","display_name":"Learning message-passing inference machines for structured prediction","publication_year":2011,"publication_date":"2011-06-01","ids":{"openalex":"https://openalex.org/W2070797946","doi":"https://doi.org/10.1109/cvpr.2011.5995724","mag":"2070797946"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2011.5995724","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2011.5995724","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"CVPR 2011","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://figshare.com/articles/journal_contribution/Learning_Message-Passing_Inference_Machines_for_Structured_Prediction/6555350","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5057087592","display_name":"St\u00e9phane Ross","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Stephane Ross","raw_affiliation_strings":["Robotics Institute, Carnegie Mellon University, USA","The Robotics Institute Carnegie-Mellon University"],"affiliations":[{"raw_affiliation_string":"Robotics Institute, Carnegie Mellon University, USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"The Robotics Institute Carnegie-Mellon University","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037345774","display_name":"Daniel Urda","orcid":"https://orcid.org/0000-0003-2662-798X"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniel Munoz","raw_affiliation_strings":["Robotics Institute, Carnegie Mellon University, USA","The Robotics Institute Carnegie-Mellon University"],"affiliations":[{"raw_affiliation_string":"Robotics Institute, Carnegie Mellon University, USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"The Robotics Institute Carnegie-Mellon University","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075246991","display_name":"Martial Hebert","orcid":"https://orcid.org/0000-0003-4566-5930"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Martial Hebert","raw_affiliation_strings":["Robotics Institute, Carnegie Mellon University, USA","The Robotics Institute Carnegie-Mellon University"],"affiliations":[{"raw_affiliation_string":"Robotics Institute, Carnegie Mellon University, USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"The Robotics Institute Carnegie-Mellon University","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112411386","display_name":"J. Andrew Bagnell","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"J. Andrew Bagnell","raw_affiliation_strings":["Robotics Institute, Carnegie Mellon University, USA","The Robotics Institute Carnegie-Mellon University"],"affiliations":[{"raw_affiliation_string":"Robotics Institute, Carnegie Mellon University, USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"The Robotics Institute Carnegie-Mellon University","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5057087592"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":5.2318,"has_fulltext":false,"cited_by_count":97,"citation_normalized_percentile":{"value":0.96397938,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"2737","last_page":"2744"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10799","display_name":"Data Visualization and Analytics","score":0.9955000281333923,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9951000213623047,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.8540371656417847},{"id":"https://openalex.org/keywords/graphical-model","display_name":"Graphical model","score":0.8214576244354248},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7564576864242554},{"id":"https://openalex.org/keywords/belief-propagation","display_name":"Belief propagation","score":0.6767073273658752},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6741317510604858},{"id":"https://openalex.org/keywords/message-passing","display_name":"Message passing","score":0.5806576609611511},{"id":"https://openalex.org/keywords/structured-prediction","display_name":"Structured prediction","score":0.5733016729354858},{"id":"https://openalex.org/keywords/approximate-inference","display_name":"Approximate inference","score":0.5253384113311768},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5248708128929138},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5109843015670776},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5003492832183838},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4997751712799072},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.449381560087204},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3558533787727356}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.8540371656417847},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.8214576244354248},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7564576864242554},{"id":"https://openalex.org/C152948882","wikidata":"https://www.wikidata.org/wiki/Q4060686","display_name":"Belief propagation","level":3,"score":0.6767073273658752},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6741317510604858},{"id":"https://openalex.org/C854659","wikidata":"https://www.wikidata.org/wiki/Q1859284","display_name":"Message passing","level":2,"score":0.5806576609611511},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.5733016729354858},{"id":"https://openalex.org/C2777472644","wikidata":"https://www.wikidata.org/wiki/Q16968992","display_name":"Approximate inference","level":3,"score":0.5253384113311768},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5248708128929138},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5109843015670776},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5003492832183838},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4997751712799072},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.449381560087204},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3558533787727356},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1109/cvpr.2011.5995724","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2011.5995724","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"CVPR 2011","raw_type":"proceedings-article"},{"id":"pmh:oai:repository.cmu.edu:robotics-1818","is_oa":false,"landing_page_url":"http://repository.cmu.edu/robotics/819","pdf_url":null,"source":{"id":"https://openalex.org/S4306400668","display_name":"Research Showcase @ Carnegie Mellon University (Carnegie Mellon University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I74973139","host_organization_name":"Carnegie Mellon University","host_organization_lineage":["https://openalex.org/I74973139"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Robotics Institute","raw_type":"text"},{"id":"pmh:doi:10.1184/r1/6555350","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":null,"raw_type":"Journal contribution"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.204.3481","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.204.3481","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.ri.cmu.edu/pub_files/2011/6/ross_cvpr_11.pdf","raw_type":"text"},{"id":"pmh:oai:figshare.com:article/6555350","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/Learning_Message-Passing_Inference_Machines_for_Structured_Prediction/6555350","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},{"id":"doi:10.1184/r1/6555350.v1","is_oa":true,"landing_page_url":"https://doi.org/10.1184/r1/6555350.v1","pdf_url":null,"source":{"id":"https://openalex.org/S7407050927","display_name":"KiltHub Repository","issn_l":null,"issn":[],"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"pmh:oai:figshare.com:article/6555350","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/Learning_Message-Passing_Inference_Machines_for_Structured_Prediction/6555350","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320333591","display_name":"Multidisciplinary University Research Initiative","ror":null},{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1497193185","https://openalex.org/W1525888637","https://openalex.org/W1569657508","https://openalex.org/W1581592866","https://openalex.org/W1902270342","https://openalex.org/W2072128103","https://openalex.org/W2092423930","https://openalex.org/W2096920988","https://openalex.org/W2099608971","https://openalex.org/W2105644991","https://openalex.org/W2112796928","https://openalex.org/W2114412769","https://openalex.org/W2116877738","https://openalex.org/W2125310925","https://openalex.org/W2129259959","https://openalex.org/W2142641780","https://openalex.org/W2143516773","https://openalex.org/W2147880316","https://openalex.org/W2148852318","https://openalex.org/W2158349948","https://openalex.org/W2159080219","https://openalex.org/W2159213092","https://openalex.org/W2159992248","https://openalex.org/W2962957031","https://openalex.org/W4231109964","https://openalex.org/W6631424144","https://openalex.org/W6634230617","https://openalex.org/W6635091746","https://openalex.org/W6639676470","https://openalex.org/W6675004785","https://openalex.org/W6675041964","https://openalex.org/W6675760969","https://openalex.org/W6677125801","https://openalex.org/W6679262086","https://openalex.org/W6680724558","https://openalex.org/W6682082992","https://openalex.org/W6683537246"],"related_works":["https://openalex.org/W4297812452","https://openalex.org/W2129270363","https://openalex.org/W959529772","https://openalex.org/W2612895134","https://openalex.org/W2163364417","https://openalex.org/W1614580364","https://openalex.org/W2962950510","https://openalex.org/W2153267847","https://openalex.org/W3208681360","https://openalex.org/W2077621940"],"abstract_inverted_index":{"Nearly":[0],"every":[1],"structured":[2],"prediction":[3],"problem":[4],"in":[5],"computer":[6],"vision":[7],"requires":[8],"approximate":[9,35],"inference":[10,36,62,71,138],"due":[11,53],"to":[12,54,119,130,148],"large":[13],"and":[14,29,88,156,166],"complex":[15],"dependencies":[16],"among":[17],"output":[18,120],"labels.":[19],"While":[20],"graphical":[21,65,132],"models":[22,33],"provide":[23],"a":[24,44,64,74,106,131],"clean":[25],"separation":[26],"between":[27],"modeling":[28],"inference,":[30],"learning":[31],"these":[32],"with":[34,140],"is":[37,47],"not":[38],"well":[39],"understood.":[40],"Furthermore,":[41],"even":[42],"if":[43],"good":[45],"model":[46,133],"learned,":[48],"predictions":[49],"are":[50],"often":[51],"inaccurate":[52],"approximations.":[55],"In":[56],"this":[57],"work,":[58],"instead":[59,68],"of":[60,76,117,158],"performing":[61],"over":[63,105],"model,":[66],"we":[67,79,111],"consider":[69],"the":[70,115,121,154],"procedure":[72],"as":[73,85,95],"composition":[75],"predictors.":[77],"Specifically,":[78],"focus":[80],"on":[81,161],"message-passing":[82],"algorithms,":[83],"such":[84],"Belief":[86],"Propagation,":[87],"show":[89],"how":[90],"they":[91],"can":[92,112,145],"be":[93,146],"viewed":[94],"procedures":[96],"that":[97,144],"sequentially":[98],"predict":[99],"label":[100],"distributions":[101],"at":[102],"each":[103],"node":[104],"graph.":[107],"Given":[108],"labeled":[109],"graphs,":[110],"then":[113],"train":[114],"sequence":[116],"predictors":[118],"correct":[122],"labeling":[123],"s.":[124],"The":[125],"result":[126],"no":[127],"longer":[128],"corresponds":[129],"but":[134],"simply":[135],"defines":[136],"an":[137],"procedure,":[139],"strong":[141],"theoretical":[142],"properties,":[143],"used":[147],"classify":[149],"new":[150],"graphs.":[151],"We":[152],"demonstrate":[153],"scalability":[155],"efficacy":[157],"our":[159],"approach":[160],"3D":[162,167],"point":[163],"cloud":[164],"classification":[165],"surface":[168],"estimation":[169],"from":[170],"single":[171],"images.":[172]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":14},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":16},{"year":2016,"cited_by_count":19},{"year":2015,"cited_by_count":11},{"year":2014,"cited_by_count":12},{"year":2013,"cited_by_count":7},{"year":2012,"cited_by_count":1}],"updated_date":"2026-04-16T15:07:20.185449","created_date":"2025-10-10T00:00:00"}