{"id":"https://openalex.org/W4224315935","doi":"https://doi.org/10.1111/rssb.12497","title":"Manifold Markov Chain Monte Carlo Methods for Bayesian Inference in Diffusion Models","display_name":"Manifold Markov Chain Monte Carlo Methods for Bayesian Inference in Diffusion Models","publication_year":2022,"publication_date":"2022-04-19","ids":{"openalex":"https://openalex.org/W4224315935","doi":"https://doi.org/10.1111/rssb.12497","mag":"2994584912"},"language":"en","primary_location":{"id":"doi:10.1111/rssb.12497","doi":"https://doi.org/10.1111/rssb.12497","is_oa":true,"landing_page_url":"https://doi.org/10.1111/rssb.12497","pdf_url":null,"source":{"id":"https://openalex.org/S145009937","display_name":"Journal of the Royal Statistical Society Series B (Statistical Methodology)","issn_l":"1369-7412","issn":["1369-7412","1467-9868"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a-star","anvur-class-a","anvur-scientific","cwts-core","dongbi-a","doyens","jufo-3","ki-jl-1","norway-2","poland-200","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the Royal Statistical Society Series B: Statistical Methodology","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1111/rssb.12497","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5039079586","display_name":"Matthew M. Graham","orcid":"https://orcid.org/0000-0001-9104-7960","observed_orcids":["https://orcid.org/0000-0001-9104-7960"]},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Matthew M. Graham","raw_affiliation_strings":["University College London , London , UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University College London , London , UK","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075419354","display_name":"Alexandre H. Thi\u00e9ry","orcid":"https://orcid.org/0000-0002-9542-509X","observed_orcids":["https://orcid.org/0000-0002-9542-509X"]},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Alexandre H. Thiery","raw_affiliation_strings":["National University of Singapore, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006951281","display_name":"Alexandros Beskos","orcid":"https://orcid.org/0000-0002-4577-8153","observed_orcids":["https://orcid.org/0000-0002-4577-8153"]},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Alexandros Beskos","raw_affiliation_strings":["University College London , London , UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University College London , London , UK","institution_ids":["https://openalex.org/I45129253"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5039079586"],"corresponding_institution_ids":["https://openalex.org/I45129253"],"apc_list":{"value":2400,"currency":"GBP","value_usd":3600},"apc_paid":{"value":2400,"currency":"GBP","value_usd":3600},"fwci":2.8137,"has_fulltext":true,"cited_by_count":30,"citation_normalized_percentile":{"value":0.9260355,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":99},"biblio":{"volume":"84","issue":"4","first_page":"1229","last_page":"1256"},"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":1.0,"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":1.0,"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":0.0,"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.0,"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/bayesian-inference","display_name":"Bayesian inference","score":0.6399999856948853},{"id":"https://openalex.org/keywords/nonlinear-diffusion","display_name":"nonlinear diffusion","score":0.7350000143051147},{"id":"https://openalex.org/keywords/posterior-inference","display_name":"posterior inference","score":0.5270000100135803},{"id":"https://openalex.org/keywords/measurement-noise","display_name":"measurement noise","score":0.4690000116825104}],"concepts":[{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.6338858008384705},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.550713062286377},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.525805652141571},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.489890992641449},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.48205313086509705},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.46467286348342896},{"id":"https://openalex.org/C13153151","wikidata":"https://www.wikidata.org/wiki/Q1639846","display_name":"Hybrid Monte Carlo","level":4,"score":0.4392227530479431},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.3989967703819275},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.39057457447052},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3537865877151489},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34083008766174316},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23906159400939941},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.14589357376098633},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10627761483192444}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1111/rssb.12497","doi":"https://doi.org/10.1111/rssb.12497","is_oa":true,"landing_page_url":"https://doi.org/10.1111/rssb.12497","pdf_url":null,"source":{"id":"https://openalex.org/S145009937","display_name":"Journal of the Royal Statistical Society Series B (Statistical Methodology)","issn_l":"1369-7412","issn":["1369-7412","1467-9868"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a-star","anvur-class-a","anvur-scientific","cwts-core","dongbi-a","doyens","jufo-3","ki-jl-1","norway-2","poland-200","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the Royal Statistical Society Series B: Statistical Methodology","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1912.02982","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1912.02982","pdf_url":"https://arxiv.org/pdf/1912.02982","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":null,"raw_type":"text"},{"id":"mag:2994584912","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/pdf/1912.02982.pdf","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},{"id":"pmh:oai:eprints.ucl.ac.uk.OAI2:10141906","doi":null,"is_oa":false,"landing_page_url":"https://discovery.ucl.ac.uk/id/eprint/10141906/","pdf_url":null,"source":{"id":"https://openalex.org/S4306400024","display_name":"UCL Discovery (University College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I45129253","host_organization_name":"University College London","host_organization_lineage":["https://openalex.org/I45129253"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of the Royal Statistical Society: Series B (Statistical Methodology) , 84 (4) pp. 1229-1256. (2022)","raw_type":"Article"},{"id":"doi:10.48550/arxiv.1912.02982","doi":"https://doi.org/10.48550/arxiv.1912.02982","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1912.02982","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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.1111/rssb.12497","doi":"https://doi.org/10.1111/rssb.12497","is_oa":true,"landing_page_url":"https://doi.org/10.1111/rssb.12497","pdf_url":null,"source":{"id":"https://openalex.org/S145009937","display_name":"Journal of the Royal Statistical Society Series B (Statistical Methodology)","issn_l":"1369-7412","issn":["1369-7412","1467-9868"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a-star","anvur-class-a","anvur-scientific","cwts-core","dongbi-a","doyens","jufo-3","ki-jl-1","norway-2","poland-200","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the Royal Statistical Society Series B: Statistical Methodology","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320319993","display_name":"Leverhulme Trust","ror":"https://ror.org/012mzw131"},{"id":"https://openalex.org/F4320320295","display_name":"Newcastle University","ror":"https://ror.org/01kj2bm70"},{"id":"https://openalex.org/F4320325699","display_name":"Lloyd's Register","ror":"https://ror.org/03hhbk905"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4224315935.pdf","grobid_xml":"https://content.openalex.org/works/W4224315935.grobid-xml"},"referenced_works_count":68,"referenced_works":["https://openalex.org/W610242975","https://openalex.org/W621546036","https://openalex.org/W1496599205","https://openalex.org/W1505052663","https://openalex.org/W1545319692","https://openalex.org/W1567796607","https://openalex.org/W1585773866","https://openalex.org/W1857053476","https://openalex.org/W1977482735","https://openalex.org/W1979619742","https://openalex.org/W1981514681","https://openalex.org/W1982482186","https://openalex.org/W1997628954","https://openalex.org/W2005549295","https://openalex.org/W2009375605","https://openalex.org/W2011301426","https://openalex.org/W2011795318","https://openalex.org/W2025262040","https://openalex.org/W2027140414","https://openalex.org/W2059448777","https://openalex.org/W2061191702","https://openalex.org/W2088413985","https://openalex.org/W2090805023","https://openalex.org/W2106706098","https://openalex.org/W2120575449","https://openalex.org/W2126479355","https://openalex.org/W2129728285","https://openalex.org/W2134589175","https://openalex.org/W2137945003","https://openalex.org/W2138565515","https://openalex.org/W2143792696","https://openalex.org/W2153701468","https://openalex.org/W2156520836","https://openalex.org/W2170316986","https://openalex.org/W2182075968","https://openalex.org/W2228030579","https://openalex.org/W2241732996","https://openalex.org/W2318135321","https://openalex.org/W2323178299","https://openalex.org/W2359271261","https://openalex.org/W2428735145","https://openalex.org/W2462335633","https://openalex.org/W2478429860","https://openalex.org/W2486999229","https://openalex.org/W2546505240","https://openalex.org/W2572702041","https://openalex.org/W2594587955","https://openalex.org/W2597403478","https://openalex.org/W2772813568","https://openalex.org/W2820111529","https://openalex.org/W2888855694","https://openalex.org/W2894906643","https://openalex.org/W2906421926","https://openalex.org/W2910719176","https://openalex.org/W2920804790","https://openalex.org/W2963977107","https://openalex.org/W2964109039","https://openalex.org/W2964121744","https://openalex.org/W3003257820","https://openalex.org/W3088699253","https://openalex.org/W3125937912","https://openalex.org/W3176807509","https://openalex.org/W4230123783","https://openalex.org/W4231021340","https://openalex.org/W4249083122","https://openalex.org/W4298134445","https://openalex.org/W4388322878","https://openalex.org/W6912261041"],"related_works":["https://openalex.org/W2994584912","https://openalex.org/W2883751584","https://openalex.org/W6991032860","https://openalex.org/W3125672409","https://openalex.org/W2134589175","https://openalex.org/W2088413985","https://openalex.org/W146235782","https://openalex.org/W2126750122","https://openalex.org/W7099053639","https://openalex.org/W2952448409"],"abstract_inverted_index":{"Abstract":[0],"Bayesian":[1],"inference":[2,105],"for":[3,106],"nonlinear":[4],"diffusions,":[5],"observed":[6,111],"at":[7,189],"discrete":[8],"times,":[9],"is":[10,126,187],"a":[11,20,32,88,107,137,160],"challenging":[12],"task":[13],"that":[14,167],"has":[15],"prompted":[16],"the":[17,26,46,59,64,95,122,163,171,177,185],"development":[18],"of":[19,22,49,58,63,69,87,109,139,162,173,179],"number":[21,178],"algorithms,":[23],"mainly":[24],"within":[25],"computational":[27,43],"statistics":[28],"community.":[29],"We":[30],"propose":[31,159],"new":[33],"direction,":[34],"and":[35,42,53,68,133,176],"accompanying":[36],"methodology\u2014borrowing":[37],"ideas":[38],"from":[39],"statistical":[40],"physics":[41],"chemistry\u2014for":[44],"inferring":[45],"posterior":[47],"distribution":[48],"latent":[50],"diffusion":[51,73,112],"paths":[52,74],"model":[54],"parameters,":[55,70],"given":[56],"observations":[57,146],"process.":[60],"Joint":[61],"configurations":[62],"underlying":[65],"process":[66],"noise":[67],"mapping":[71],"onto":[72],"consistent":[75],"with":[76,117,147,165],"observations,":[77],"form":[78],"an":[79],"implicitly":[80],"defined":[81],"manifold.":[82],"Then,":[83],"by":[84],"making":[85],"use":[86],"constrained":[89],"Hamiltonian":[90],"Monte":[91],"Carlo":[92],"algorithm":[93],"on":[94],"embedded":[96],"manifold,":[97],"we":[98,158],"are":[99],"able":[100],"to":[101],"perform":[102],"computationally":[103],"efficient":[104],"class":[108],"discretely":[110],"models.":[113],"Critically,":[114],"in":[115,121,136,170],"contrast":[116],"other":[118],"approaches":[119],"proposed":[120],"literature,":[123],"our":[124],"methodology":[125],"highly":[127],"automated,":[128],"requiring":[129],"minimal":[130],"user":[131],"intervention":[132],"applying":[134],"alike":[135],"range":[138],"settings,":[140],"including:":[141],"elliptic":[142],"or":[143,148,152],"hypo-elliptic":[144],"systems;":[145],"without":[149],"noise;":[150],"linear":[151],"non-linear":[153],"observation":[154,180],"operators.":[155],"Exploiting":[156],"Markovianity,":[157],"variant":[161],"method":[164],"complexity":[166],"scales":[168],"linearly":[169],"resolution":[172],"path":[174],"discretisation":[175],"times.":[181],"Python":[182],"code":[183],"reproducing":[184],"results":[186],"available":[188],"http://doi.org/10.5281/zenodo.5796148.":[190]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":1}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2022-04-26T00:00:00"}
