{"id":"https://openalex.org/W7164529803","doi":"https://doi.org/10.48550/arxiv.2606.13260","title":"Extracting Governing Equations from Latent Dynamics via Multi-View Contrastive Learning","display_name":"Extracting Governing Equations from Latent Dynamics via Multi-View Contrastive Learning","publication_year":2026,"publication_date":"2026-06-11","ids":{"openalex":"https://openalex.org/W7164529803","doi":"https://doi.org/10.48550/arxiv.2606.13260"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.13260","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.13260","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":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.13260","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017710357","display_name":"Paolo Muratore","orcid":"https://orcid.org/0000-0003-4520-5950"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Muratore, Paolo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5025196309","display_name":"Mackenzie Weygandt Mathis","orcid":"https://orcid.org/0000-0001-7368-4456"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mathis, Mackenzie Weygandt","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":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"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/T11206","display_name":"Model Reduction and Neural Networks","score":0.5455999970436096,"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"}},"topics":[{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.5455999970436096,"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/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.32659998536109924,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.016699999570846558,"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/identifiability","display_name":"Identifiability","score":0.8780999779701233},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5292999744415283},{"id":"https://openalex.org/keywords/affine-transformation","display_name":"Affine transformation","score":0.43529999256134033},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.428600013256073},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.42080000042915344},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4049000144004822},{"id":"https://openalex.org/keywords/dynamical-systems-theory","display_name":"Dynamical systems theory","score":0.39959999918937683},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.3993000090122223},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.39399999380111694}],"concepts":[{"id":"https://openalex.org/C122770356","wikidata":"https://www.wikidata.org/wiki/Q1656753","display_name":"Identifiability","level":2,"score":0.8780999779701233},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5436999797821045},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5292999744415283},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4867999851703644},{"id":"https://openalex.org/C92757383","wikidata":"https://www.wikidata.org/wiki/Q382497","display_name":"Affine transformation","level":2,"score":0.43529999256134033},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.428600013256073},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.42080000042915344},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4049000144004822},{"id":"https://openalex.org/C79379906","wikidata":"https://www.wikidata.org/wiki/Q3174497","display_name":"Dynamical systems theory","level":2,"score":0.39959999918937683},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.3993000090122223},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3986000120639801},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.39399999380111694},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.37779998779296875},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35989999771118164},{"id":"https://openalex.org/C145912823","wikidata":"https://www.wikidata.org/wiki/Q113558","display_name":"Dynamics (music)","level":2,"score":0.35679998993873596},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3280999958515167},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.3276999890804291},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.3208000063896179},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.30000001192092896},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.29840001463890076},{"id":"https://openalex.org/C33962884","wikidata":"https://www.wikidata.org/wiki/Q378637","display_name":"Dynamical system (definition)","level":3,"score":0.29179999232292175},{"id":"https://openalex.org/C119247159","wikidata":"https://www.wikidata.org/wiki/Q1366192","display_name":"System identification","level":3,"score":0.28600001335144043},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.2759000062942505},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.27410000562667847},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.27090001106262207},{"id":"https://openalex.org/C22157029","wikidata":"https://www.wikidata.org/wiki/Q17080460","display_name":"Nonlinear system identification","level":4,"score":0.26429998874664307},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.259799987077713},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.25459998846054077}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.13260","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.13260","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":"doi:10.48550/arxiv.2606.13260","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.13260","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":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.597981870174408}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Identifying":[0],"latent":[1,35,114],"dynamical":[2,124],"systems":[3],"from":[4,41,58],"noisy,":[5],"high-dimensional":[6],"measurements":[7],"is":[8],"a":[9,26,65,120],"central":[10],"problem":[11],"at":[12],"the":[13,38,51,62,76,100,138],"intersection":[14],"of":[15,50,75,103,112,123],"representation":[16],"learning,":[17],"system":[18],"identification,":[19],"and":[20,37,116,129,134],"scientific":[21],"discovery.":[22],"We":[23,83],"present":[24],"DYSCO,":[25],"multi-view":[27],"temporal":[28],"contrastive":[29],"learning":[30],"algorithm":[31],"that":[32],"jointly":[33],"recovers":[34],"trajectories":[36,115],"governing":[39,77],"dynamics":[40,63],"such":[42],"observations,":[43],"by":[44],"leveraging":[45],"multiple":[46],"independent":[47],"noisy":[48,104],"views":[49],"same":[52],"underlying":[53],"process":[54],"to":[55,91,99],"disentangle":[56],"signal":[57],"noise.":[59],"By":[60],"parameterizing":[61],"in":[64],"structured":[66],"functional":[67],"basis,":[68],"our":[69],"framework":[70],"further":[71],"enables":[72],"symbolic":[73],"recovery":[74,111],"equations":[78],"within":[79],"an":[80,92],"affine":[81,93],"gauge.":[82],"offer":[84],"theoretical":[85],"guarantees":[86],"for":[87,143],"strong":[88],"identification":[89],"up":[90],"indeterminacy,":[94],"extending":[95],"prior":[96],"identifiability":[97],"results":[98],"realistic":[101],"setting":[102],"nonlinear":[105],"observations.":[106],"Empirically,":[107],"we":[108],"demonstrate":[109],"accurate":[110],"both":[113,132],"flow":[117],"fields":[118],"across":[119],"diverse":[121],"set":[122],"regimes":[125],"(e.g.,":[126],"chaotic,":[127],"oscillatory,":[128],"metastable)":[130],"under":[131],"Gaussian":[133],"Poisson":[135],"observation":[136],"noise,":[137],"latter":[139],"being":[140],"particularly":[141],"relevant":[142],"neural":[144],"recordings.":[145]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-13T00:00:00"}