{"id":"https://openalex.org/W4403487391","doi":"https://doi.org/10.3233/faia240844","title":"Subsystem Discovery in High-Dimensional Time-Series Using Masked Autoencoders","display_name":"Subsystem Discovery in High-Dimensional Time-Series Using Masked Autoencoders","publication_year":2024,"publication_date":"2024-10-16","ids":{"openalex":"https://openalex.org/W4403487391","doi":"https://doi.org/10.3233/faia240844"},"language":"en","primary_location":{"id":"doi:10.3233/faia240844","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia240844","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA240844","source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"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":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA240844","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5034135638","display_name":"Teemu Sarapisto","orcid":null},"institutions":[{"id":"https://openalex.org/I133731052","display_name":"University of Helsinki","ror":"https://ror.org/040af2s02","country_code":"FI","type":"education","lineage":["https://openalex.org/I133731052"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Teemu Sarapisto","raw_affiliation_strings":["Department of Computer Science, University of Helsinki"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Helsinki","institution_ids":["https://openalex.org/I133731052"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033882642","display_name":"Haoyu Wei","orcid":null},"institutions":[{"id":"https://openalex.org/I133731052","display_name":"University of Helsinki","ror":"https://ror.org/040af2s02","country_code":"FI","type":"education","lineage":["https://openalex.org/I133731052"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Haoyu Wei","raw_affiliation_strings":["Department of Computer Science, University of Helsinki"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Helsinki","institution_ids":["https://openalex.org/I133731052"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078732211","display_name":"Keijo Heljanko","orcid":"https://orcid.org/0000-0002-4547-2701"},"institutions":[{"id":"https://openalex.org/I133731052","display_name":"University of Helsinki","ror":"https://ror.org/040af2s02","country_code":"FI","type":"education","lineage":["https://openalex.org/I133731052"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Keijo Heljanko","raw_affiliation_strings":["Department of Computer Science, University of Helsinki"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Helsinki","institution_ids":["https://openalex.org/I133731052"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084783731","display_name":"Arto Klami","orcid":"https://orcid.org/0000-0002-7950-1355"},"institutions":[{"id":"https://openalex.org/I133731052","display_name":"University of Helsinki","ror":"https://ror.org/040af2s02","country_code":"FI","type":"education","lineage":["https://openalex.org/I133731052"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Arto Klami","raw_affiliation_strings":["Department of Computer Science, University of Helsinki"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Helsinki","institution_ids":["https://openalex.org/I133731052"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021445018","display_name":"Laura Ruotsalainen","orcid":"https://orcid.org/0000-0002-4057-4143"},"institutions":[{"id":"https://openalex.org/I133731052","display_name":"University of Helsinki","ror":"https://ror.org/040af2s02","country_code":"FI","type":"education","lineage":["https://openalex.org/I133731052"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Laura Ruotsalainen","raw_affiliation_strings":["Department of Computer Science, University of Helsinki"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Helsinki","institution_ids":["https://openalex.org/I133731052"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"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":0.41216795,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9865000247955322,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9865000247955322,"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/T10320","display_name":"Neural Networks and Applications","score":0.9480000138282776,"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/series","display_name":"Series (stratigraphy)","score":0.762516975402832},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4716726243495941},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41368672251701355},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39525362849235535},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.11071670055389404},{"id":"https://openalex.org/keywords/paleontology","display_name":"Paleontology","score":0.03469684720039368}],"concepts":[{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.762516975402832},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4716726243495941},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41368672251701355},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39525362849235535},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.11071670055389404},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.03469684720039368}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/faia240844","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia240844","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA240844","source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"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":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"}],"best_oa_location":{"id":"doi:10.3233/faia240844","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia240844","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA240844","source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"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":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4403487391.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"Deep":[0],"neural":[1],"networks":[2],"are":[3],"increasingly":[4],"used":[5],"for":[6,86],"time":[7],"series":[8],"tasks,":[9],"yet":[10],"they":[11],"often":[12],"struggle":[13],"to":[14,29],"interpretably":[15],"model":[16,139],"high-dimensional":[17,130],"data.":[18,43,132],"In":[19,133],"this":[20],"context,":[21],"we":[22,113,135],"consider":[23],"the":[24,107,116,138],"task":[25],"of":[26,72,77,125],"learning":[27],"easy":[28],"understand":[30],"connections":[31],"between":[32,56],"time-series":[33,48],"variables,":[34],"and":[35,82,103,122],"organizing":[36],"them":[37],"into":[38],"subsystems,":[39],"directly":[40],"from":[41,119,129],"observed":[42],"Our":[44,95],"approach":[45],"reconstructs":[46],"multivariate":[47],"with":[49,91],"a":[50,62,99],"masked":[51],"autoencoder,":[52],"where":[53],"all":[54],"information":[55],"individual":[57],"variables":[58,73],"is":[59,83],"mediated":[60],"by":[61],"learned":[63],"adjacency":[64],"matrix.":[65],"This":[66],"intuitive":[67],"pairwise":[68],"relationship":[69],"enables":[70],"grouping":[71],"without":[74],"prior":[75],"knowledge":[76],"cluster":[78],"quantity":[79],"or":[80],"size,":[81],"particularly":[84],"useful":[85,100],"analyzing":[87],"complex":[88],"sensor":[89],"systems":[90],"unknown":[92],"structural":[93],"interdependencies.":[94],"method":[96],"simultaneously":[97],"learns":[98],"signal":[101],"representation":[102],"aids":[104],"in":[105],"understanding":[106],"underlying":[108],"processes.":[109],"We":[110],"show":[111,136],"that":[112,137],"can":[114],"learn":[115],"correct":[117],"subsystems":[118],"simulated":[120],"data,":[121],"demonstrate":[123],"identification":[124],"plausible":[126],"subsystem":[127],"structure":[128],"real-world":[131],"addition,":[134],"retains":[140],"high":[141],"predictive":[142],"performance.":[143]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}