{"id":"https://openalex.org/W2119618626","doi":"https://doi.org/10.1145/2185520.2185552","title":"Synthesizing open worlds with constraints using locally annealed reversible jump MCMC","display_name":"Synthesizing open worlds with constraints using locally annealed reversible jump MCMC","publication_year":2012,"publication_date":"2012-07-01","ids":{"openalex":"https://openalex.org/W2119618626","doi":"https://doi.org/10.1145/2185520.2185552","mag":"2119618626"},"language":"en","primary_location":{"id":"doi:10.1145/2185520.2185552","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2185520.2185552","pdf_url":null,"source":{"id":"https://openalex.org/S185367456","display_name":"ACM Transactions on Graphics","issn_l":"0730-0301","issn":["0730-0301","1557-7368"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Graphics","raw_type":"journal-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/A5082965827","display_name":"Yi\u2010Ting Yeh","orcid":"https://orcid.org/0000-0003-3002-3425"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yi-Ting Yeh","raw_affiliation_strings":["Stanford University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stanford University","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100604251","display_name":"Lingfeng Yang","orcid":"https://orcid.org/0000-0002-2725-8947"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lingfeng Yang","raw_affiliation_strings":["Stanford University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stanford University","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015095497","display_name":"Matthew Watson","orcid":"https://orcid.org/0000-0001-6375-3905"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Matthew Watson","raw_affiliation_strings":["Stanford University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stanford University","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001961716","display_name":"Noah D. Goodman","orcid":"https://orcid.org/0000-0002-9176-8802"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Noah D. Goodman","raw_affiliation_strings":["Stanford University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stanford University","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018111215","display_name":"Pat Hanrahan","orcid":"https://orcid.org/0000-0002-3474-9752"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pat Hanrahan","raw_affiliation_strings":["Stanford University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stanford University","institution_ids":["https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":9.4398,"has_fulltext":false,"cited_by_count":130,"citation_normalized_percentile":{"value":0.98438988,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"31","issue":"4","first_page":"1","last_page":"11"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9975000023841858,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9975000023841858,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9918000102043152,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9876000285148621,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.8324825763702393},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6625651717185974},{"id":"https://openalex.org/keywords/reversible-jump-markov-chain-monte-carlo","display_name":"Reversible-jump Markov chain Monte Carlo","score":0.6563554406166077},{"id":"https://openalex.org/keywords/jump","display_name":"Jump","score":0.5464954376220703},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.5358492136001587},{"id":"https://openalex.org/keywords/factor","display_name":"Factor (programming language)","score":0.5128079056739807},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.507112979888916},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.49524274468421936},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.4672166109085083},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.45214468240737915},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.43781787157058716},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4290882349014282},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4173649549484253},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3669339418411255},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2648490071296692},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2021186649799347},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.1523556113243103},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.09686344861984253},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08307912945747375},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.07781553268432617}],"concepts":[{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.8324825763702393},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6625651717185974},{"id":"https://openalex.org/C2780591659","wikidata":"https://www.wikidata.org/wiki/Q17083869","display_name":"Reversible-jump Markov chain Monte Carlo","level":4,"score":0.6563554406166077},{"id":"https://openalex.org/C2780695682","wikidata":"https://www.wikidata.org/wiki/Q4005959","display_name":"Jump","level":2,"score":0.5464954376220703},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.5358492136001587},{"id":"https://openalex.org/C2781039887","wikidata":"https://www.wikidata.org/wiki/Q1391724","display_name":"Factor (programming language)","level":2,"score":0.5128079056739807},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.507112979888916},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.49524274468421936},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.4672166109085083},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.45214468240737915},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.43781787157058716},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4290882349014282},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4173649549484253},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3669339418411255},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2648490071296692},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2021186649799347},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.1523556113243103},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.09686344861984253},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08307912945747375},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.07781553268432617},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"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/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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2185520.2185552","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2185520.2185552","pdf_url":null,"source":{"id":"https://openalex.org/S185367456","display_name":"ACM Transactions on Graphics","issn_l":"0730-0301","issn":["0730-0301","1557-7368"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Graphics","raw_type":"journal-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.361.6215","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.361.6215","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.stanford.edu/~ngoodman/papers/owl.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.4099999964237213,"display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G1651507167","display_name":null,"funder_award_id":"N00014-09-1-0124","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"},{"id":"https://openalex.org/G6266292046","display_name":null,"funder_award_id":"HR0011-11-C-0007-P00003","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"}],"funders":[{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"},{"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":27,"referenced_works":["https://openalex.org/W113525123","https://openalex.org/W128101668","https://openalex.org/W194123052","https://openalex.org/W390299538","https://openalex.org/W1480311453","https://openalex.org/W1517555081","https://openalex.org/W1890754682","https://openalex.org/W1968983388","https://openalex.org/W1977970897","https://openalex.org/W2020999234","https://openalex.org/W2043719428","https://openalex.org/W2073412813","https://openalex.org/W2103815986","https://openalex.org/W2106706098","https://openalex.org/W2114350394","https://openalex.org/W2130634053","https://openalex.org/W2137813581","https://openalex.org/W2138309709","https://openalex.org/W2149846167","https://openalex.org/W2165497092","https://openalex.org/W2170694982","https://openalex.org/W2232528854","https://openalex.org/W3138514142","https://openalex.org/W3139355527","https://openalex.org/W4285719527","https://openalex.org/W6604569386","https://openalex.org/W6639796194"],"related_works":["https://openalex.org/W2953867467","https://openalex.org/W3151507825","https://openalex.org/W2001857141","https://openalex.org/W2951072873","https://openalex.org/W1554021357","https://openalex.org/W2146317212","https://openalex.org/W2493909506","https://openalex.org/W2112913028","https://openalex.org/W2494638202","https://openalex.org/W2076092328"],"abstract_inverted_index":{"We":[0,19,56,129],"present":[1],"a":[2,23,58],"novel":[3],"Markov":[4],"chain":[5],"Monte":[6],"Carlo":[7],"(MCMC)":[8],"algorithm":[9],"that":[10],"generates":[11],"samples":[12],"from":[13],"transdimensional":[14],"distributions":[15,62],"encoding":[16],"complex":[17],"constraints.":[18,96],"use":[20],"factor":[21,54],"graphs,":[22],"type":[24],"of":[25,45,52,60,86,104,112,123,133],"graphical":[26],"model,":[27],"to":[28,69],"encode":[29],"constraints":[30],"as":[31,95],"factors.":[32],"Our":[33],"proposed":[34],"MCMC":[35],"method,":[36],"called":[37],"locally":[38],"annealed":[39,61],"reversible":[40],"jump":[41],"MCMC,":[42],"exploits":[43],"knowledge":[44],"how":[46],"dimension":[47],"changes":[48],"affect":[49],"the":[50,53,64,71,84,102,110,131],"structure":[51],"graph.":[55],"employ":[57],"sequence":[59],"during":[63],"sampling":[65],"process,":[66],"allowing":[67],"us":[68],"explore":[70],"state":[72],"space":[73],"across":[74],"different":[75,121],"dimensionalities":[76],"more":[77],"freely.":[78],"This":[79],"approach":[80,135],"is":[81],"motivated":[82],"by":[83],"application":[85],"layout":[87,140],"synthesis":[88,141],"where":[89,109],"relationships":[90],"between":[91],"objects":[92,113,124],"are":[93,114],"characterized":[94],"In":[97],"particular,":[98],"our":[99,134],"method":[100],"addresses":[101],"challenge":[103],"synthesizing":[105],"open":[106,138],"world":[107,139],"layouts":[108],"number":[111],"not":[115],"fixed":[116],"and":[117,145],"optimal":[118],"configurations":[119],"for":[120],"numbers":[122],"may":[125],"be":[126],"drastically":[127],"different.":[128],"demonstrate":[130],"applicability":[132],"on":[136],"two":[137],"problems:":[142],"coffee":[143],"shops":[144],"golf":[146],"courses.":[147]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":12},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":13},{"year":2017,"cited_by_count":10},{"year":2016,"cited_by_count":10},{"year":2015,"cited_by_count":11},{"year":2014,"cited_by_count":11},{"year":2013,"cited_by_count":10},{"year":2012,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}