{"id":"https://openalex.org/W2051768929","doi":"https://doi.org/10.1109/icassp.2013.6638879","title":"Particle metropolis hastings using Langevin dynamics","display_name":"Particle metropolis hastings using Langevin dynamics","publication_year":2013,"publication_date":"2013-05-01","ids":{"openalex":"https://openalex.org/W2051768929","doi":"https://doi.org/10.1109/icassp.2013.6638879","mag":"2051768929"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2013.6638879","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2013.6638879","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Acoustics, Speech and Signal Processing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-93699","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5089607178","display_name":"Johan Dahlin","orcid":"https://orcid.org/0000-0002-9424-1272"},"institutions":[{"id":"https://openalex.org/I102134673","display_name":"Link\u00f6ping University","ror":"https://ror.org/05ynxx418","country_code":"SE","type":"education","lineage":["https://openalex.org/I102134673"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Johan Dahlin","raw_affiliation_strings":["Division of Automatic Control, Link\u00f6ping University, Linkoping, Sweden","Div. of Autom. Control, Linkoping Univ., Link\u00f6ping, Sweden#TAB#"],"affiliations":[{"raw_affiliation_string":"Division of Automatic Control, Link\u00f6ping University, Linkoping, Sweden","institution_ids":["https://openalex.org/I102134673"]},{"raw_affiliation_string":"Div. of Autom. Control, Linkoping Univ., Link\u00f6ping, Sweden#TAB#","institution_ids":["https://openalex.org/I102134673"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045048407","display_name":"Fredrik Lindsten","orcid":"https://orcid.org/0000-0003-3749-5820"},"institutions":[{"id":"https://openalex.org/I102134673","display_name":"Link\u00f6ping University","ror":"https://ror.org/05ynxx418","country_code":"SE","type":"education","lineage":["https://openalex.org/I102134673"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Fredrik Lindsten","raw_affiliation_strings":["Division of Automatic Control, Link\u00f6ping University, Linkoping, Sweden","Div. of Autom. Control, Linkoping Univ., Link\u00f6ping, Sweden#TAB#"],"affiliations":[{"raw_affiliation_string":"Division of Automatic Control, Link\u00f6ping University, Linkoping, Sweden","institution_ids":["https://openalex.org/I102134673"]},{"raw_affiliation_string":"Div. of Autom. Control, Linkoping Univ., Link\u00f6ping, Sweden#TAB#","institution_ids":["https://openalex.org/I102134673"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083090794","display_name":"Thomas B. Sch\u00f6n","orcid":"https://orcid.org/0000-0001-5183-234X"},"institutions":[{"id":"https://openalex.org/I102134673","display_name":"Link\u00f6ping University","ror":"https://ror.org/05ynxx418","country_code":"SE","type":"education","lineage":["https://openalex.org/I102134673"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Thomas B. Schon","raw_affiliation_strings":["Division of Automatic Control, Link\u00f6ping University, Linkoping, Sweden","Div. of Autom. Control, Linkoping Univ., Link\u00f6ping, Sweden#TAB#"],"affiliations":[{"raw_affiliation_string":"Division of Automatic Control, Link\u00f6ping University, Linkoping, Sweden","institution_ids":["https://openalex.org/I102134673"]},{"raw_affiliation_string":"Div. of Autom. Control, Linkoping Univ., Link\u00f6ping, Sweden#TAB#","institution_ids":["https://openalex.org/I102134673"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5089607178"],"corresponding_institution_ids":["https://openalex.org/I102134673"],"apc_list":null,"apc_paid":null,"fwci":5.159,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.95880597,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"6308","last_page":"6312"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12056","display_name":"Markov Chains and Monte Carlo Methods","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12056","display_name":"Markov Chains and Monte Carlo Methods","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9983000159263611,"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":0.9955999851226807,"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/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.7661713361740112},{"id":"https://openalex.org/keywords/random-walk","display_name":"Random walk","score":0.7557719945907593},{"id":"https://openalex.org/keywords/statistical-physics","display_name":"Statistical physics","score":0.7294860482215881},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.6750757098197937},{"id":"https://openalex.org/keywords/metropolis\u2013hastings-algorithm","display_name":"Metropolis\u2013Hastings algorithm","score":0.6719613671302795},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.5879920721054077},{"id":"https://openalex.org/keywords/stochastic-volatility","display_name":"Stochastic volatility","score":0.5361632704734802},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.490372896194458},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4871089458465576},{"id":"https://openalex.org/keywords/hybrid-monte-carlo","display_name":"Hybrid Monte Carlo","score":0.4851270616054535},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.4477354884147644},{"id":"https://openalex.org/keywords/volatility","display_name":"Volatility (finance)","score":0.2680176794528961},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2514229118824005},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.23813417553901672},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.22022220492362976},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.21573936939239502},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.19628900289535522},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.11576315760612488},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.07205376029014587}],"concepts":[{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.7661713361740112},{"id":"https://openalex.org/C121194460","wikidata":"https://www.wikidata.org/wiki/Q856741","display_name":"Random walk","level":2,"score":0.7557719945907593},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.7294860482215881},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.6750757098197937},{"id":"https://openalex.org/C204693719","wikidata":"https://www.wikidata.org/wiki/Q910810","display_name":"Metropolis\u2013Hastings algorithm","level":4,"score":0.6719613671302795},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.5879920721054077},{"id":"https://openalex.org/C85393063","wikidata":"https://www.wikidata.org/wiki/Q596307","display_name":"Stochastic volatility","level":3,"score":0.5361632704734802},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.490372896194458},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4871089458465576},{"id":"https://openalex.org/C13153151","wikidata":"https://www.wikidata.org/wiki/Q1639846","display_name":"Hybrid Monte Carlo","level":4,"score":0.4851270616054535},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.4477354884147644},{"id":"https://openalex.org/C91602232","wikidata":"https://www.wikidata.org/wiki/Q756115","display_name":"Volatility (finance)","level":2,"score":0.2680176794528961},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2514229118824005},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.23813417553901672},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.22022220492362976},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.21573936939239502},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.19628900289535522},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.11576315760612488},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.07205376029014587}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/icassp.2013.6638879","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2013.6638879","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Acoustics, Speech and Signal Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.308.2554","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.308.2554","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://users.isy.liu.se/en/rt/schon/Publications/DahlinLS2013.pdf","raw_type":"text"},{"id":"pmh:oai:DiVA.org:liu-93699","is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-93699","pdf_url":null,"source":{"id":"https://openalex.org/S4306401559","display_name":"KTH Publication Database DiVA (KTH Royal Institute of Technology)","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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference paper"}],"best_oa_location":{"id":"pmh:oai:DiVA.org:liu-93699","is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-93699","pdf_url":null,"source":{"id":"https://openalex.org/S4306401559","display_name":"KTH Publication Database DiVA (KTH Royal Institute of Technology)","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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference paper"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.5099999904632568}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W977039283","https://openalex.org/W1480376833","https://openalex.org/W1501586228","https://openalex.org/W1512805107","https://openalex.org/W1534630418","https://openalex.org/W1545319692","https://openalex.org/W1571438983","https://openalex.org/W1618715392","https://openalex.org/W1830883013","https://openalex.org/W1883186006","https://openalex.org/W1965828084","https://openalex.org/W1988827501","https://openalex.org/W2001355407","https://openalex.org/W2002067385","https://openalex.org/W2010522529","https://openalex.org/W2014652454","https://openalex.org/W2031294093","https://openalex.org/W2059448777","https://openalex.org/W2069739265","https://openalex.org/W2077611006","https://openalex.org/W2091860746","https://openalex.org/W2103582908","https://openalex.org/W2106961326","https://openalex.org/W2111787305","https://openalex.org/W2125764009","https://openalex.org/W2125862452","https://openalex.org/W2131598171","https://openalex.org/W2143737806","https://openalex.org/W2151804552","https://openalex.org/W2478027467","https://openalex.org/W2612956293","https://openalex.org/W2949651744","https://openalex.org/W2954040150","https://openalex.org/W3021146541","https://openalex.org/W3100622648","https://openalex.org/W4232114885","https://openalex.org/W4244486013","https://openalex.org/W4250389103","https://openalex.org/W4298304654","https://openalex.org/W6638674303","https://openalex.org/W6678872406"],"related_works":["https://openalex.org/W4226314133","https://openalex.org/W3098348269","https://openalex.org/W3000025630","https://openalex.org/W4214552121","https://openalex.org/W3037147032","https://openalex.org/W4248057375","https://openalex.org/W4288028892","https://openalex.org/W2959831473","https://openalex.org/W3037866298","https://openalex.org/W2986820836"],"abstract_inverted_index":{"Particle":[0],"Markov":[1],"Chain":[2],"Monte":[3,63],"Carlo":[4,64],"(PMCMC)":[5],"samplers":[6],"allow":[7],"for":[8,22],"routine":[9],"inference":[10],"of":[11,39,56,76],"parameters":[12],"and":[13,107],"states":[14],"in":[15,53],"challenging":[16],"nonlinear":[17],"problems.":[18],"A":[19],"common":[20],"choice":[21],"the":[23,37,51,54,57,61,69,94,108],"parameter":[24],"proposal":[25,85],"is":[26,99],"a":[27,78,82,103],"simple":[28],"random":[29,83],"walk":[30,84],"sampler,":[31],"which":[32],"can":[33,73],"scale":[34],"poorly":[35],"with":[36],"number":[38],"parameters.":[40],"In":[41],"this":[42],"paper,":[43],"we":[44],"propose":[45],"to":[46,60,68,80,93,102],"use":[47],"log-likelihood":[48],"gradients,":[49],"i.e.":[50],"score,":[52],"construction":[55],"proposal,":[58],"akin":[59],"Langevin":[62],"method,":[65],"but":[66],"adapted":[67],"PMCMC":[70],"framework.":[71],"This":[72],"be":[74],"thought":[75],"as":[77],"way":[79],"guide":[81],"by":[86],"using":[87],"drift":[88,109],"terms":[89],"that":[90],"are":[91],"proportional":[92],"score":[95],"function.":[96],"The":[97],"method":[98],"successfully":[100],"applied":[101],"stochastic":[104],"volatility":[105],"model":[106],"term":[110],"exhibits":[111],"intuitive":[112],"behaviour.":[113]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":6},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":8},{"year":2013,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
