{"id":"https://openalex.org/W4391691973","doi":"https://doi.org/10.1007/s10618-024-01006-1","title":"Universal representation learning for multivariate time series using the instance-level and cluster-level supervised contrastive learning","display_name":"Universal representation learning for multivariate time series using the instance-level and cluster-level supervised contrastive learning","publication_year":2024,"publication_date":"2024-02-09","ids":{"openalex":"https://openalex.org/W4391691973","doi":"https://doi.org/10.1007/s10618-024-01006-1","pmid":"https://pubmed.ncbi.nlm.nih.gov/39949582"},"language":"en","primary_location":{"id":"doi:10.1007/s10618-024-01006-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10618-024-01006-1","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10618-024-01006-1.pdf","source":{"id":"https://openalex.org/S121920818","display_name":"Data Mining and Knowledge Discovery","issn_l":"1384-5810","issn":["1384-5810","1573-756X"],"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":"Data Mining and Knowledge Discovery","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10618-024-01006-1.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5072674174","display_name":"Nazanin Moradinasab","orcid":"https://orcid.org/0000-0003-3881-8599"},"institutions":[{"id":"https://openalex.org/I4210116219","display_name":"Engineering Systems (United States)","ror":"https://ror.org/02qg60849","country_code":"US","type":"company","lineage":["https://openalex.org/I4210116219"]},{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Nazanin Moradinasab","raw_affiliation_strings":["Department of Engineering Systems and Environment, University of Virginia, Charlottesville, VA 22904, USA","Department of Engineering Systems and Environment, University of Virginia, Charlottesville, VA, 22904, USA"],"raw_orcid":"https://orcid.org/0000-0003-3881-8599","affiliations":[{"raw_affiliation_string":"Department of Engineering Systems and Environment, University of Virginia, Charlottesville, VA 22904, USA","institution_ids":["https://openalex.org/I4210116219","https://openalex.org/I51556381"]},{"raw_affiliation_string":"Department of Engineering Systems and Environment, University of Virginia, Charlottesville, VA, 22904, USA","institution_ids":["https://openalex.org/I4210116219","https://openalex.org/I51556381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024765749","display_name":"Suchetha Sharma","orcid":null},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Suchetha Sharma","raw_affiliation_strings":["School of Data Science, University of Virginia, Charlottesville, VA 22904, USA","School of Data Science, University of Virginia, Charlottesville, VA, 22904, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Data Science, University of Virginia, Charlottesville, VA 22904, USA","institution_ids":["https://openalex.org/I51556381"]},{"raw_affiliation_string":"School of Data Science, University of Virginia, Charlottesville, VA, 22904, USA","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009744089","display_name":"Ronen Bar\u2010Yoseph","orcid":"https://orcid.org/0000-0002-0055-5415"},"institutions":[{"id":"https://openalex.org/I204250578","display_name":"University of California, Irvine","ror":"https://ror.org/04gyf1771","country_code":"US","type":"education","lineage":["https://openalex.org/I204250578"]},{"id":"https://openalex.org/I2801301638","display_name":"Rambam Health Care Campus","ror":"https://ror.org/01fm87m50","country_code":"IL","type":"healthcare","lineage":["https://openalex.org/I2801301638"]}],"countries":["IL","US"],"is_corresponding":false,"raw_author_name":"Ronen Bar-Yoseph","raw_affiliation_strings":["Pediatric Exercise and Genomics Research Center, University of California, Irvine, CA 92697, USA","Pediatric Pulmonary Institute, Ruth Rappaport Children's Hospital, Rambam Health Care Campus, 3109601 Haifa, Israel","Pediatric Exercise and Genomics Research Center, University of California, Irvine, CA, 92697, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pediatric Exercise and Genomics Research Center, University of California, Irvine, CA 92697, USA","institution_ids":["https://openalex.org/I204250578"]},{"raw_affiliation_string":"Pediatric Pulmonary Institute, Ruth Rappaport Children's Hospital, Rambam Health Care Campus, 3109601 Haifa, Israel","institution_ids":["https://openalex.org/I2801301638"]},{"raw_affiliation_string":"Pediatric Exercise and Genomics Research Center, University of California, Irvine, CA, 92697, USA","institution_ids":["https://openalex.org/I204250578"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033468427","display_name":"Shlomit Radom\u2010Aizik","orcid":"https://orcid.org/0009-0004-4023-7026"},"institutions":[{"id":"https://openalex.org/I204250578","display_name":"University of California, Irvine","ror":"https://ror.org/04gyf1771","country_code":"US","type":"education","lineage":["https://openalex.org/I204250578"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shlomit Radom-Aizik","raw_affiliation_strings":["Pediatric Exercise and Genomics Research Center, University of California, Irvine, CA 92697, USA","Pediatric Exercise and Genomics Research Center, University of California, Irvine, CA, 92697, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pediatric Exercise and Genomics Research Center, University of California, Irvine, CA 92697, USA","institution_ids":["https://openalex.org/I204250578"]},{"raw_affiliation_string":"Pediatric Exercise and Genomics Research Center, University of California, Irvine, CA, 92697, USA","institution_ids":["https://openalex.org/I204250578"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063695524","display_name":"Kenneth C. Bilchick","orcid":"https://orcid.org/0000-0002-5188-3603"},"institutions":[{"id":"https://openalex.org/I2799765794","display_name":"University of Virginia Health System","ror":"https://ror.org/00wn7d965","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I2799765794"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kenneth C. Bilchick","raw_affiliation_strings":["Cardiovascular Division, Department of Medicine, University of Virginia Health System, Charlottesville, VA 22903, USA","Cardiovascular Division, Department of Medicine, University of Virginia Health System, Charlottesville, VA, 22903, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cardiovascular Division, Department of Medicine, University of Virginia Health System, Charlottesville, VA 22903, USA","institution_ids":["https://openalex.org/I2799765794"]},{"raw_affiliation_string":"Cardiovascular Division, Department of Medicine, University of Virginia Health System, Charlottesville, VA, 22903, USA","institution_ids":["https://openalex.org/I2799765794"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024191718","display_name":"Dan M. Cooper","orcid":"https://orcid.org/0000-0003-4022-0043"},"institutions":[{"id":"https://openalex.org/I204250578","display_name":"University of California, Irvine","ror":"https://ror.org/04gyf1771","country_code":"US","type":"education","lineage":["https://openalex.org/I204250578"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dan M. Cooper","raw_affiliation_strings":["Institute for Clinical and Translational Science, University of California, Irvine, CA 92697, USA","Pediatric Exercise and Genomics Research Center, University of California, Irvine, CA 92697, USA","Pediatric Exercise and Genomics Research Center, University of California, Irvine, CA, 92697, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Clinical and Translational Science, University of California, Irvine, CA 92697, USA","institution_ids":["https://openalex.org/I204250578"]},{"raw_affiliation_string":"Pediatric Exercise and Genomics Research Center, University of California, Irvine, CA 92697, USA","institution_ids":["https://openalex.org/I204250578"]},{"raw_affiliation_string":"Pediatric Exercise and Genomics Research Center, University of California, Irvine, CA, 92697, USA","institution_ids":["https://openalex.org/I204250578"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047868387","display_name":"Arthur Weltman","orcid":"https://orcid.org/0000-0002-0125-3769"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Arthur Weltman","raw_affiliation_strings":["Department of Kinesiology, University of Virginia, Charlottesville, VA 22903, USA","Division of Endocrinology and Metabolism, Department of Medicine, University of Virginia, Charlottesville, VA 22903, USA","Department of Kinesiology, University of Virginia, Charlottesville, VA, 22903, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Kinesiology, University of Virginia, Charlottesville, VA 22903, USA","institution_ids":["https://openalex.org/I51556381"]},{"raw_affiliation_string":"Division of Endocrinology and Metabolism, Department of Medicine, University of Virginia, Charlottesville, VA 22903, USA","institution_ids":["https://openalex.org/I51556381"]},{"raw_affiliation_string":"Department of Kinesiology, University of Virginia, Charlottesville, VA, 22903, USA","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086462231","display_name":"Donald E. Brown","orcid":"https://orcid.org/0000-0002-9140-2632"},"institutions":[{"id":"https://openalex.org/I4210116219","display_name":"Engineering Systems (United States)","ror":"https://ror.org/02qg60849","country_code":"US","type":"company","lineage":["https://openalex.org/I4210116219"]},{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Donald E. Brown","raw_affiliation_strings":["Department of Engineering Systems and Environment, University of Virginia, Charlottesville, VA 22904, USA","School of Data Science, University of Virginia, Charlottesville, VA 22904, USA","School of Data Science, University of Virginia, Charlottesville, VA, 22904, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Engineering Systems and Environment, University of Virginia, Charlottesville, VA 22904, USA","institution_ids":["https://openalex.org/I4210116219","https://openalex.org/I51556381"]},{"raw_affiliation_string":"School of Data Science, University of Virginia, Charlottesville, VA 22904, USA","institution_ids":["https://openalex.org/I51556381"]},{"raw_affiliation_string":"School of Data Science, University of Virginia, Charlottesville, VA, 22904, USA","institution_ids":["https://openalex.org/I51556381"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5072674174"],"corresponding_institution_ids":["https://openalex.org/I4210116219","https://openalex.org/I51556381"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":1.9729,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.85808196,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"38","issue":"3","first_page":"1493","last_page":"1519"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9998999834060669,"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":0.9998999834060669,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9876000285148621,"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/T11309","display_name":"Music and Audio Processing","score":0.9815999865531921,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.7234981656074524},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.611364483833313},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5946181416511536},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5857957601547241},{"id":"https://openalex.org/keywords/cluster","display_name":"Cluster (spacecraft)","score":0.5590988993644714},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5052888989448547},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48666197061538696},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4762863516807556},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39979287981987}],"concepts":[{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.7234981656074524},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.611364483833313},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5946181416511536},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5857957601547241},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.5590988993644714},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5052888989448547},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48666197061538696},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4762863516807556},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39979287981987},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1007/s10618-024-01006-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10618-024-01006-1","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10618-024-01006-1.pdf","source":{"id":"https://openalex.org/S121920818","display_name":"Data Mining and Knowledge Discovery","issn_l":"1384-5810","issn":["1384-5810","1573-756X"],"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":"Data Mining and Knowledge Discovery","raw_type":"journal-article"},{"id":"pmid:39949582","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/39949582","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data mining and knowledge discovery","raw_type":null},{"id":"pmh:oai:escholarship.org:ark:/13030/qt3729t0t9","is_oa":true,"landing_page_url":"https://escholarship.org/uc/item/3729t0t9","pdf_url":"https://escholarship.org/content/qt3729t0t9/qt3729t0t9.pdf","source":{"id":"https://openalex.org/S4306400115","display_name":"eScholarship (California Digital Library)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2801248553","host_organization_name":"California Digital Library","host_organization_lineage":["https://openalex.org/I2801248553"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Data Mining and Knowledge Discovery, vol 38, iss 3","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:11825059","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11825059","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11825059/pdf/nihms-2002028.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Data Min Knowl Discov","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1007/s10618-024-01006-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10618-024-01006-1","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10618-024-01006-1.pdf","source":{"id":"https://openalex.org/S121920818","display_name":"Data Mining and Knowledge Discovery","issn_l":"1384-5810","issn":["1384-5810","1573-756X"],"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":"Data Mining and Knowledge Discovery","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6800000071525574,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G1832261870","display_name":null,"funder_award_id":"UL1TR003015/ KL2TR003016","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G6681907667","display_name":null,"funder_award_id":"UL1TR003015/ KL2TR003016","funder_id":"https://openalex.org/F4320337472","funder_display_name":"National Center for Advancing Translational Sciences"},{"id":"https://openalex.org/G7312491463","display_name":null,"funder_award_id":"UL1TR003015","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G788917307","display_name":null,"funder_award_id":"KL2TR003016","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"}],"funders":[{"id":"https://openalex.org/F4320310536","display_name":"University of Virginia","ror":"https://ror.org/0153tk833"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320332688","display_name":"University of California, Irvine","ror":"https://ror.org/04gyf1771"},{"id":"https://openalex.org/F4320337472","display_name":"National Center for Advancing Translational Sciences","ror":"https://ror.org/04pw6fb54"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4391691973.pdf"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W789250018","https://openalex.org/W1853995153","https://openalex.org/W2026909728","https://openalex.org/W2029438113","https://openalex.org/W2066224818","https://openalex.org/W2118371392","https://openalex.org/W2171393861","https://openalex.org/W2283896980","https://openalex.org/W2293031124","https://openalex.org/W2402972623","https://openalex.org/W2468738844","https://openalex.org/W2524083015","https://openalex.org/W2551393996","https://openalex.org/W2581867724","https://openalex.org/W2749165076","https://openalex.org/W2783323081","https://openalex.org/W2888791883","https://openalex.org/W2892035503","https://openalex.org/W2962858109","https://openalex.org/W2972810968","https://openalex.org/W2998010409","https://openalex.org/W3004401633","https://openalex.org/W3037722545","https://openalex.org/W3064187906","https://openalex.org/W3083891030","https://openalex.org/W3084430883","https://openalex.org/W3098967488","https://openalex.org/W3115948762","https://openalex.org/W3162900173","https://openalex.org/W3186145246","https://openalex.org/W3199148273","https://openalex.org/W4285240208","https://openalex.org/W4291178938","https://openalex.org/W4295755966","https://openalex.org/W4313019631"],"related_works":["https://openalex.org/W2406638334","https://openalex.org/W1991765889","https://openalex.org/W1990068454","https://openalex.org/W2472172556","https://openalex.org/W1919101720","https://openalex.org/W1570805059","https://openalex.org/W2357266745","https://openalex.org/W1578824628","https://openalex.org/W4390961098","https://openalex.org/W2118640767"],"abstract_inverted_index":{"The":[0,33,273,311],"multivariate":[1,139,164,213],"time":[2,16,122,140,165,214,308],"series":[3,123,215,309],"classification":[4,124,130],"(MTSC)":[5],"task":[6],"aims":[7],"to":[8,41,53,88,158,180,201,205,269,278,323],"predict":[9],"a":[10,14,63,115,351],"class":[11],"label":[12],"for":[13,30,121,147,184,212,223],"given":[15,225],"series.":[17,166],"Recently,":[18],"modern":[19],"deep":[20],"learning-based":[21],"approaches":[22,37,200,330],"have":[23],"achieved":[24],"promising":[25],"performance":[26,131],"over":[27],"traditional":[28],"methods":[29],"MTSC":[31],"tasks.":[32],"success":[34],"of":[35,45,66,138,163,313,336,355],"these":[36,95],"relies":[38],"on":[39,153,250,295,317,344,353],"access":[40],"the":[42,129,134,160,185,194,207,218,231,234,239,254,270,280,304,314,334,337,342,345,356,366],"massive":[43,64],"amount":[44,65],"labeled":[46,67,92],"data":[47,68,93,183],"(i.e.,":[48],"annotating":[49],"or":[50],"assigning":[51],"tags":[52],"each":[54,224,260,283],"sample":[55],"that":[56,105,228,349],"shows":[57],"its":[58,143,321],"corresponding":[59],"category).":[60],"However,":[61,253],"obtaining":[62],"is":[69,151,257,339],"usually":[70],"very":[71],"time-consuming":[72],"and":[73,142,174,187,196,209,246,262,285,303],"expensive":[74],"in":[75,102,331],"many":[76],"real-world":[77,305],"applications":[78],"such":[79],"as":[80,244,267],"medicine,":[81],"because":[82],"it":[83],"requires":[84],"domain":[85],"experts'":[86],"knowledge":[87],"annotate":[89],"data.":[90],"Insufficient":[91],"prevents":[94],"models":[96],"from":[97,230,238],"learning":[98,120,133,199,221],"discriminative":[99,135,208,326],"features,":[100],"resulting":[101],"poor":[103],"margins":[104],"reduce":[106],"generalization":[107],"performance.":[108],"To":[109],"address":[110],"this":[111,292],"challenge,":[112],"we":[113,192],"propose":[114,193],"novel":[116,293],"approach:":[117],"supervised":[118,154],"contrastive":[119,155],"(SupCon-TSC).":[125],"This":[126],"approach":[127,256,294],"improves":[128],"by":[132,361],"low-dimensional":[136],"representations":[137],"series,":[141],"end-to-end":[144],"structure":[145,162],"allows":[146],"interpretable":[148],"outcomes.":[149],"It":[150],"based":[152,249],"(SupCon)":[156],"loss":[157,276],"learn":[159,206,324],"inherent":[161],"First,":[167],"two":[168,296],"separate":[169],"augmentation":[170,176],"families,":[171],"including":[172],"strong":[173],"weak":[175],"methods,":[177],"are":[178,242],"utilized":[179],"generate":[181],"augmented":[182],"source":[186,232],"target":[188,240],"networks,":[189],"respectively.":[190],"Second,":[191],"instance-level,":[195],"cluster-level":[197,255,274],"SupCon":[198,220,275],"capture":[202],"contextual":[203],"information":[204],"universal":[210,357],"representation":[211,358],"datasets.":[216],"In":[217],"instance-level":[219,271],"approach,":[222],"anchor":[226],"instance":[227,261,284],"comes":[229],"network,":[233],"low-variance":[235],"output":[236],"encodings":[237],"network":[241],"sampled":[243],"positive":[245],"negative":[247],"instances":[248],"their":[251],"labels.":[252],"performed":[258],"between":[259,282],"cluster":[263,286],"centers":[264,287],"among":[265,288],"batches,":[266],"opposed":[268],"approach.":[272],"attempts":[277],"maximize":[279],"similarities":[281],"batches.":[289],"We":[290],"tested":[291],"small":[297],"cardiopulmonary":[298],"exercise":[299],"testing":[300],"(CPET)":[301],"datasets":[302,319],"UEA":[306,346],"Multivariate":[307],"archive.":[310],"results":[312,343],"SupCon-TSC":[315],"model":[316],"CPET":[318],"indicate":[320],"capability":[322],"more":[325],"features":[327,359],"than":[328],"existing":[329],"situations":[332],"where":[333],"size":[335],"dataset":[338],"small.":[340],"Moreover,":[341],"archive":[347],"show":[348],"training":[350],"classifier":[352],"top":[354],"learned":[360],"our":[362],"proposed":[363],"method":[364],"outperforms":[365],"state-of-the-art":[367],"approaches.":[368]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":1}],"updated_date":"2026-01-13T01:12:25.745995","created_date":"2025-10-10T00:00:00"}
