{"id":"https://openalex.org/W7134826867","doi":"https://doi.org/10.48550/arxiv.2603.06752","title":"Latent Autoencoder Ensemble Kalman Filter for Nonlinear Data assimilation","display_name":"Latent Autoencoder Ensemble Kalman Filter for Nonlinear Data assimilation","publication_year":2026,"publication_date":"2026-03-06","ids":{"openalex":"https://openalex.org/W7134826867","doi":"https://doi.org/10.48550/arxiv.2603.06752"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2603.06752","is_oa":true,"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":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5128630067","display_name":"Xin T. Tong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tong, Xin T.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128679561","display_name":"Yanyan Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yanyan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128659754","display_name":"Liang Yan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yan, Liang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.28320076,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10466","display_name":"Meteorological Phenomena and Simulations","score":0.8370000123977661,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10466","display_name":"Meteorological Phenomena and Simulations","score":0.8370000123977661,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.07169999927282333,"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.010300000198185444,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/data-assimilation","display_name":"Data assimilation","score":0.7883999943733215},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.7174000144004822},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.660099983215332},{"id":"https://openalex.org/keywords/ensemble-kalman-filter","display_name":"Ensemble Kalman filter","score":0.6061999797821045},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.5418000221252441},{"id":"https://openalex.org/keywords/extended-kalman-filter","display_name":"Extended Kalman filter","score":0.5034000277519226},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.38749998807907104},{"id":"https://openalex.org/keywords/chaotic","display_name":"Chaotic","score":0.3571000099182129}],"concepts":[{"id":"https://openalex.org/C24552861","wikidata":"https://www.wikidata.org/wiki/Q2670177","display_name":"Data assimilation","level":2,"score":0.7883999943733215},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.7174000144004822},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.660099983215332},{"id":"https://openalex.org/C79334102","wikidata":"https://www.wikidata.org/wiki/Q3072268","display_name":"Ensemble Kalman filter","level":4,"score":0.6061999797821045},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5504999756813049},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.5418000221252441},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.515500009059906},{"id":"https://openalex.org/C206833254","wikidata":"https://www.wikidata.org/wiki/Q5421817","display_name":"Extended Kalman filter","level":3,"score":0.5034000277519226},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42080000042915344},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.38749998807907104},{"id":"https://openalex.org/C2777052490","wikidata":"https://www.wikidata.org/wiki/Q5072826","display_name":"Chaotic","level":2,"score":0.3571000099182129},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.3513000011444092},{"id":"https://openalex.org/C58024561","wikidata":"https://www.wikidata.org/wiki/Q207721","display_name":"Latent heat","level":2,"score":0.35109999775886536},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.34689998626708984},{"id":"https://openalex.org/C8639503","wikidata":"https://www.wikidata.org/wiki/Q6059511","display_name":"Invariant extended Kalman filter","level":4,"score":0.32429999113082886},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.322299987077713},{"id":"https://openalex.org/C150679823","wikidata":"https://www.wikidata.org/wiki/Q5436946","display_name":"Fast Kalman filter","level":4,"score":0.31709998846054077},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.3118000030517578},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3077000081539154},{"id":"https://openalex.org/C65965080","wikidata":"https://www.wikidata.org/wiki/Q1806885","display_name":"Latent variable model","level":3,"score":0.2768999934196472},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.27160000801086426},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.26179999113082886},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.25940001010894775},{"id":"https://openalex.org/C75649859","wikidata":"https://www.wikidata.org/wiki/Q148877","display_name":"Assimilation (phonology)","level":2,"score":0.25}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2603.06752","is_oa":true,"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":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2603.06752","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.06752","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2603.06752","is_oa":true,"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":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,68],"ensemble":[1,45],"Kalman":[2,30,46,105],"filter":[3,47],"(EnKF)":[4],"is":[5],"widely":[6],"used":[7],"for":[8,19,165],"data":[9],"assimilation":[10,56,130,187],"in":[11,58,95,120],"high-dimensional":[12],"systems,":[13],"but":[14],"its":[15],"performance":[16],"often":[17],"deteriorates":[18],"strongly":[20],"nonlinear":[21,73,136,174],"dynamics":[22,156],"due":[23],"to":[24,115],"the":[25,29,33,55,96,104,121,139,166,180,189],"structural":[26,143],"mismatch":[27],"between":[28],"update":[31],"and":[32,65,83,108,112,128,146,160,175,185,192,201],"underlying":[34],"system":[35],"behavior.":[36],"In":[37],"this":[38,51],"work,":[39],"we":[40],"propose":[41],"a":[42,59,72,77,84,90,150],"latent":[43,61,80,86,97,122,129,137,168],"autoencoder":[44],"(LAE-EnKF)":[48],"that":[49,132,179],"addresses":[50],"limitation":[52],"by":[53],"reformulating":[54],"problem":[57],"learned":[60],"space":[62],"with":[63,76,103,125],"linear":[64,79,92,155],"stable":[66,78,186],"dynamics.":[67],"proposed":[69,140,167],"method":[70],"learns":[71],"encoder--decoder":[74],"together":[75],"evolution":[81],"operator":[82],"consistent":[85],"observation":[87],"mapping,":[88],"yielding":[89],"closed":[91],"state-space":[93],"model":[94],"coordinates.":[98],"This":[99],"construction":[100],"restores":[101],"compatibility":[102],"filtering":[106],"framework":[107],"allows":[109],"both":[110],"forecast":[111],"analysis":[113,152],"steps":[114],"be":[116],"carried":[117],"out":[118],"entirely":[119],"space.":[123],"Compared":[124],"existing":[126],"autoencoder-based":[127],"approaches":[131],"rely":[133],"on":[134,157,172],"unconstrained":[135],"dynamics,":[138],"formulation":[141],"emphasizes":[142],"consistency,":[144],"stability,":[145],"interpretability.":[147],"We":[148],"provide":[149],"theoretical":[151],"of":[153],"learning":[154],"low-dimensional":[158],"manifolds":[159],"establish":[161],"generalization":[162],"error":[163],"bounds":[164],"model.":[169],"Numerical":[170],"experiments":[171],"representative":[173],"chaotic":[176],"systems":[177],"demonstrate":[178],"LAE-EnKF":[181],"yields":[182],"more":[183],"accurate":[184],"than":[188],"standard":[190],"EnKF":[191],"related":[193],"latent-space":[194],"methods,":[195],"while":[196],"maintaining":[197],"comparable":[198],"computational":[199],"cost":[200],"data-driven.":[202]},"counts_by_year":[],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2026-03-11T00:00:00"}