{"id":"https://openalex.org/W4403911442","doi":"https://doi.org/10.1007/s00332-024-10091-x","title":"Coherent Set Identification Via Direct Low Rank Maximum Likelihood Estimation","display_name":"Coherent Set Identification Via Direct Low Rank Maximum Likelihood Estimation","publication_year":2024,"publication_date":"2024-10-30","ids":{"openalex":"https://openalex.org/W4403911442","doi":"https://doi.org/10.1007/s00332-024-10091-x"},"language":"en","primary_location":{"id":"doi:10.1007/s00332-024-10091-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00332-024-10091-x","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00332-024-10091-x.pdf","source":{"id":"https://openalex.org/S131276044","display_name":"Journal of Nonlinear Science","issn_l":"0938-8974","issn":["0938-8974","1432-1467"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Nonlinear Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s00332-024-10091-x.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5043236416","display_name":"Robert Polzin","orcid":null},"institutions":[{"id":"https://openalex.org/I75951250","display_name":"Freie Universit\u00e4t Berlin","ror":"https://ror.org/046ak2485","country_code":"DE","type":"education","lineage":["https://openalex.org/I75951250"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Robert M. Polzin","raw_affiliation_strings":["Institute of Mathematics, Freie Universit\u00e4t Berlin, Berlin, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Mathematics, Freie Universit\u00e4t Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I75951250"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014068268","display_name":"Ilja Klebanov","orcid":"https://orcid.org/0000-0002-1911-4281"},"institutions":[{"id":"https://openalex.org/I75951250","display_name":"Freie Universit\u00e4t Berlin","ror":"https://ror.org/046ak2485","country_code":"DE","type":"education","lineage":["https://openalex.org/I75951250"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ilja Klebanov","raw_affiliation_strings":["Institute of Mathematics, Freie Universit\u00e4t Berlin, Berlin, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Mathematics, Freie Universit\u00e4t Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I75951250"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085251948","display_name":"Nikolas N\u00fcsken","orcid":"https://orcid.org/0000-0001-5415-5284"},"institutions":[{"id":"https://openalex.org/I183935753","display_name":"King's College London","ror":"https://ror.org/0220mzb33","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I183935753"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Nikolas N\u00fcsken","raw_affiliation_strings":["Department of Mathematics, King\u2019s College London, London, UK","Department of Mathematics, King's College London, London, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, King\u2019s College London, London, UK","institution_ids":["https://openalex.org/I183935753"]},{"raw_affiliation_string":"Department of Mathematics, King's College London, London, UK","institution_ids":["https://openalex.org/I183935753"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021278553","display_name":"P\u00e9ter Koltai","orcid":"https://orcid.org/0000-0002-8127-6804"},"institutions":[{"id":"https://openalex.org/I54009628","display_name":"University of Bayreuth","ror":"https://ror.org/0234wmv40","country_code":"DE","type":"education","lineage":["https://openalex.org/I54009628"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"P\u00e9ter Koltai","raw_affiliation_strings":["Department of Mathematics, University of Bayreuth, Bayreuth, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, University of Bayreuth, Bayreuth, Germany","institution_ids":["https://openalex.org/I54009628"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5043236416"],"corresponding_institution_ids":["https://openalex.org/I75951250"],"apc_list":{"value":2290,"currency":"EUR","value_usd":2890},"apc_paid":{"value":2290,"currency":"EUR","value_usd":2890},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20057322,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"35","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10244","display_name":"Chaos control and synchronization","score":0.989799976348877,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11261","display_name":"Quantum chaos and dynamical systems","score":0.9861000180244446,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5943270921707153},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.588740885257721},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.579875111579895},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.5618006587028503},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5154843926429749},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.4951297342777252},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.4378969669342041},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.4297955632209778},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3757916986942291},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.35540318489074707},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3489767909049988},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3417472541332245},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.27742767333984375},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.09999766945838928}],"concepts":[{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5943270921707153},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.588740885257721},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.579875111579895},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.5618006587028503},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5154843926429749},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.4951297342777252},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.4378969669342041},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.4297955632209778},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3757916986942291},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.35540318489074707},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3489767909049988},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3417472541332245},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.27742767333984375},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.09999766945838928},{"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s00332-024-10091-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00332-024-10091-x","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00332-024-10091-x.pdf","source":{"id":"https://openalex.org/S131276044","display_name":"Journal of Nonlinear Science","issn_l":"0938-8974","issn":["0938-8974","1432-1467"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Nonlinear Science","raw_type":"journal-article"},{"id":"pmh:oai:kclpure.kcl.ac.uk:publications/f3446df2-ce34-474a-96e6-d6c69456b961","is_oa":true,"landing_page_url":"https://kclpure.kcl.ac.uk/portal/en/publications/f3446df2-ce34-474a-96e6-d6c69456b961","pdf_url":null,"source":{"id":"https://openalex.org/S4306400216","display_name":"Research Portal (King's College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I183935753","host_organization_name":"King's College London","host_organization_lineage":["https://openalex.org/I183935753"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Polzin, R, Nusken, N, Klebanov, I & Koltai, P 2024, 'Coherent set identification via direct low rank maximum likelihood estimation', JOURNAL OF NONLINEAR SCIENCE, vol. 35, 2. https://doi.org/10.1007/s00332-024-10091-x","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"doi:10.1007/s00332-024-10091-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00332-024-10091-x","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00332-024-10091-x.pdf","source":{"id":"https://openalex.org/S131276044","display_name":"Journal of Nonlinear Science","issn_l":"0938-8974","issn":["0938-8974","1432-1467"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Nonlinear Science","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.4099999964237213,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G2077420360","display_name":null,"funder_award_id":"CRC 1114","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G4274372172","display_name":null,"funder_award_id":"235221301","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G4962813667","display_name":null,"funder_award_id":"projects A01","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"}],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4403911442.pdf","grobid_xml":"https://content.openalex.org/works/W4403911442.grobid-xml"},"referenced_works_count":58,"referenced_works":["https://openalex.org/W122721991","https://openalex.org/W649348608","https://openalex.org/W1501738873","https://openalex.org/W1511694993","https://openalex.org/W1522256480","https://openalex.org/W1533006072","https://openalex.org/W1902027874","https://openalex.org/W1970039276","https://openalex.org/W1977438596","https://openalex.org/W1981145361","https://openalex.org/W1981276685","https://openalex.org/W2000911789","https://openalex.org/W2012029966","https://openalex.org/W2025341678","https://openalex.org/W2031716212","https://openalex.org/W2039844283","https://openalex.org/W2043545458","https://openalex.org/W2048995400","https://openalex.org/W2063021109","https://openalex.org/W2076327952","https://openalex.org/W2084417387","https://openalex.org/W2084755618","https://openalex.org/W2106332299","https://openalex.org/W2114508388","https://openalex.org/W2124528613","https://openalex.org/W2134731454","https://openalex.org/W2139694940","https://openalex.org/W2140055271","https://openalex.org/W2144359569","https://openalex.org/W2159286112","https://openalex.org/W2168577777","https://openalex.org/W2268723675","https://openalex.org/W2299660775","https://openalex.org/W2412945859","https://openalex.org/W2606287176","https://openalex.org/W2782630728","https://openalex.org/W2787395547","https://openalex.org/W2903630570","https://openalex.org/W2906900897","https://openalex.org/W2963224943","https://openalex.org/W2964917500","https://openalex.org/W2979672600","https://openalex.org/W2985207252","https://openalex.org/W3098574429","https://openalex.org/W3100658280","https://openalex.org/W3103060822","https://openalex.org/W3105019514","https://openalex.org/W3105167274","https://openalex.org/W3114089334","https://openalex.org/W3121653411","https://openalex.org/W3216034703","https://openalex.org/W4206519735","https://openalex.org/W4211064163","https://openalex.org/W4213311833","https://openalex.org/W4233135949","https://openalex.org/W4249875616","https://openalex.org/W4390777185","https://openalex.org/W6837306243"],"related_works":["https://openalex.org/W2120595071","https://openalex.org/W2090147078","https://openalex.org/W2610798632","https://openalex.org/W2353424004","https://openalex.org/W3139607207","https://openalex.org/W2371827284","https://openalex.org/W2978085921","https://openalex.org/W1600683375","https://openalex.org/W2162067268","https://openalex.org/W2155160077"],"abstract_inverted_index":{"Abstract":[0],"We":[1,81],"analyze":[2],"connections":[3],"between":[4,130,163],"two":[5,142],"low":[6,58,74,88],"rank":[7,59,75,89],"modeling":[8],"approaches":[9,117],"from":[10,50,78],"the":[11,22,38,73,96,113,141,151,155],"last":[12],"decade":[13],"for":[14,62],"treating":[15],"dynamical":[16],"data.":[17,80],"The":[18,53],"first":[19],"one":[20,55],"is":[21,56,92],"coherence":[23,111],"problem":[24],"(or":[25],"coherent":[26],"set":[27],"approach),":[28],"where":[29],"groups":[30],"of":[31,40,95,110,146,168],"states":[32],"are":[33],"sought":[34],"that":[35,83,91],"evolve":[36],"under":[37],"action":[39],"a":[41,46,57,87,93,107,128,135],"stochastic":[42,63],"transition":[43],"matrix":[44,148],"in":[45,86],"way":[47],"maximally":[48],"distinguishable":[49],"other":[51],"groups.":[52],"second":[54],"factorization":[60],"approach":[61],"matrices,":[64],"called":[65],"direct":[66],"Bayesian":[67],"model":[68,90],"reduction":[69],"(DBMR),":[70],"which":[71],"estimates":[72],"factors":[76],"directly":[77],"observed":[79],"show":[82],"DBMR":[84],"results":[85],"projection":[94],"full":[97],"model,":[98],"and":[99,124,154,159,165],"exploit":[100],"this":[101,138],"insight":[102],"to":[103],"infer":[104],"bounds":[105],"on":[106],"quantitative":[108],"measure":[109],"within":[112],"reduced":[114],"model.":[115],"Both":[116],"can":[118],"be":[119],"formulated":[120],"as":[121],"optimization":[122],"problems,":[123],"we":[125],"also":[126],"prove":[127],"bound":[129],"their":[131],"respective":[132],"objectives.":[133],"On":[134],"broader":[136],"scope,":[137],"work":[139],"relates":[140],"classical":[143],"loss":[144],"functions":[145],"nonnegative":[147],"factorization,":[149],"namely":[150],"Frobenius":[152],"norm":[153],"generalized":[156],"Kullback\u2013Leibler":[157],"divergence,":[158],"suggests":[160],"new":[161],"links":[162],"likelihood-based":[164],"projection-based":[166],"estimation":[167],"probabilistic":[169],"models.":[170]},"counts_by_year":[],"updated_date":"2026-05-21T09:19:25.381259","created_date":"2025-10-10T00:00:00"}