{"id":"https://openalex.org/W3038427506","doi":"https://doi.org/10.1109/tnnls.2020.3001377","title":"Reservoir Computing Approaches for Representation and Classification of Multivariate Time Series.","display_name":"Reservoir Computing Approaches for Representation and Classification of Multivariate Time Series.","publication_year":2021,"publication_date":"2021-05-01","ids":{"openalex":"https://openalex.org/W3038427506","doi":"https://doi.org/10.1109/tnnls.2020.3001377","mag":"3038427506","pmid":"https://pubmed.ncbi.nlm.nih.gov/32598284"},"language":"en","primary_location":{"id":"pmid:32598284","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/32598284","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":"IEEE transactions on neural networks and learning systems","raw_type":null},"type":"article","indexed_in":["pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5036254733","display_name":"Filippo Maria Bianchi","orcid":"https://orcid.org/0000-0002-7145-3846"},"institutions":[{"id":"https://openalex.org/I4210107808","display_name":"NORCE Research AS","ror":"https://ror.org/02gagpf75","country_code":"NO","type":"facility","lineage":["https://openalex.org/I4210107808"]},{"id":"https://openalex.org/I78037679","display_name":"UiT The Arctic University of Norway","ror":"https://ror.org/00wge5k78","country_code":"NO","type":"education","lineage":["https://openalex.org/I78037679"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Filippo Maria Bianchi","raw_affiliation_strings":["Department of Physics and Technology, UiT\u2014The Arctic University of Norway, Troms\u00f8, Norway","NORCE Norwegian Research Centre, Bergen, Norway"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Physics and Technology, UiT\u2014The Arctic University of Norway, Troms\u00f8, Norway","institution_ids":["https://openalex.org/I78037679"]},{"raw_affiliation_string":"NORCE Norwegian Research Centre, Bergen, Norway","institution_ids":["https://openalex.org/I4210107808"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022153057","display_name":"Simone Scardapane","orcid":"https://orcid.org/0000-0003-0881-8344"},"institutions":[{"id":"https://openalex.org/I861853513","display_name":"Sapienza University of Rome","ror":"https://ror.org/02be6w209","country_code":"IT","type":"education","lineage":["https://openalex.org/I861853513"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Simone Scardapane","raw_affiliation_strings":["Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, Rome, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, Rome, Italy","institution_ids":["https://openalex.org/I861853513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013696891","display_name":"Sigurd L\u00f8kse","orcid":"https://orcid.org/0000-0002-1953-4315"},"institutions":[{"id":"https://openalex.org/I78037679","display_name":"UiT The Arctic University of Norway","ror":"https://ror.org/00wge5k78","country_code":"NO","type":"education","lineage":["https://openalex.org/I78037679"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Sigurd Lokse","raw_affiliation_strings":["Department of Physics and Technology, UiT\u2014The Arctic University of Norway, Troms\u00f8, Norway"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Physics and Technology, UiT\u2014The Arctic University of Norway, Troms\u00f8, Norway","institution_ids":["https://openalex.org/I78037679"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013414039","display_name":"Robert Jenssen","orcid":"https://orcid.org/0000-0002-7496-8474"},"institutions":[{"id":"https://openalex.org/I78037679","display_name":"UiT The Arctic University of Norway","ror":"https://ror.org/00wge5k78","country_code":"NO","type":"education","lineage":["https://openalex.org/I78037679"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Robert Jenssen","raw_affiliation_strings":["Department of Physics and Technology, UiT\u2014The Arctic University of Norway, Troms\u00f8, Norway"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Physics and Technology, UiT\u2014The Arctic University of Norway, Troms\u00f8, Norway","institution_ids":["https://openalex.org/I78037679"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":16.6425,"has_fulltext":false,"cited_by_count":211,"citation_normalized_percentile":{"value":0.99323572,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"32","issue":"5","first_page":"2169","last_page":"2179"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.9987000226974487,"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"}},"topics":[{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.9987000226974487,"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/T10320","display_name":"Neural Networks and Applications","score":0.9955999851226807,"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/T10581","display_name":"Neural dynamics and brain function","score":0.9692999720573425,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7245700359344482},{"id":"https://openalex.org/keywords/reservoir-computing","display_name":"Reservoir computing","score":0.6885119676589966},{"id":"https://openalex.org/keywords/python","display_name":"Python (programming language)","score":0.6391650438308716},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6199434995651245},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5260543823242188},{"id":"https://openalex.org/keywords/modular-design","display_name":"Modular design","score":0.498551607131958},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.4898545444011688},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.47774046659469604},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.4741760492324829},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.47352835536003113},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.4456357955932617},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4224069118499756},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3977113366127014},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3813505172729492},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3383736312389374},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.2550768554210663}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7245700359344482},{"id":"https://openalex.org/C135796866","wikidata":"https://www.wikidata.org/wiki/Q7315328","display_name":"Reservoir computing","level":4,"score":0.6885119676589966},{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.6391650438308716},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6199434995651245},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5260543823242188},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.498551607131958},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.4898545444011688},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.47774046659469604},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4741760492324829},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.47352835536003113},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.4456357955932617},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4224069118499756},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3977113366127014},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3813505172729492},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3383736312389374},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.2550768554210663},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"pmid:32598284","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/32598284","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":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W789250018","https://openalex.org/W1469859527","https://openalex.org/W1501306604","https://openalex.org/W1522301498","https://openalex.org/W1533861849","https://openalex.org/W1565218449","https://openalex.org/W1591801644","https://openalex.org/W1815076433","https://openalex.org/W1902688491","https://openalex.org/W1908962573","https://openalex.org/W1967541074","https://openalex.org/W1970861901","https://openalex.org/W1979856704","https://openalex.org/W1989185482","https://openalex.org/W2011667925","https://openalex.org/W2024165284","https://openalex.org/W2033268097","https://openalex.org/W2035104901","https://openalex.org/W2050493487","https://openalex.org/W2064675550","https://openalex.org/W2066224818","https://openalex.org/W2071198194","https://openalex.org/W2079735306","https://openalex.org/W2095705004","https://openalex.org/W2103179919","https://openalex.org/W2125790506","https://openalex.org/W2130942839","https://openalex.org/W2143612262","https://openalex.org/W2144994235","https://openalex.org/W2157331557","https://openalex.org/W2163614729","https://openalex.org/W2171865010","https://openalex.org/W2215770505","https://openalex.org/W2237307454","https://openalex.org/W2294059674","https://openalex.org/W2294916050","https://openalex.org/W2295142501","https://openalex.org/W2397306716","https://openalex.org/W2406585103","https://openalex.org/W2473420485","https://openalex.org/W2510380565","https://openalex.org/W2510434276","https://openalex.org/W2551393996","https://openalex.org/W2555077524","https://openalex.org/W2584197249","https://openalex.org/W2586160710","https://openalex.org/W2604269166","https://openalex.org/W2611445505","https://openalex.org/W2612810742","https://openalex.org/W2619033034","https://openalex.org/W2754051771","https://openalex.org/W2784579605","https://openalex.org/W2792332872","https://openalex.org/W2842511635","https://openalex.org/W2892035503","https://openalex.org/W2962907613","https://openalex.org/W2963912395","https://openalex.org/W2964121744","https://openalex.org/W3100270150","https://openalex.org/W3101923990","https://openalex.org/W3104901183","https://openalex.org/W4294648124","https://openalex.org/W4297808394"],"related_works":["https://openalex.org/W4378214616","https://openalex.org/W1995622179","https://openalex.org/W1484111231","https://openalex.org/W1909208367","https://openalex.org/W1552543208","https://openalex.org/W2994280181","https://openalex.org/W2074396517","https://openalex.org/W2166963679","https://openalex.org/W2187269125","https://openalex.org/W1641615907"],"abstract_inverted_index":{"Classification":[0],"of":[1,13,21,35,65,89,98,108],"multivariate":[2],"time":[3,178],"series":[4,179],"(MTS)":[5],"has":[6],"been":[7],"tackled":[8],"with":[9,113,148,169],"a":[10,18,31,55,99,105,136,141],"large":[11],"variety":[12],"methodologies":[14],"and":[15,123,177,186],"applied":[16],"to":[17,29,60,85,103,129,159],"wide":[19],"range":[20],"scenarios.":[22],"Reservoir":[23],"computing":[24],"(RC)":[25],"provides":[26,156],"efficient":[27],"tools":[28],"generate":[30],"vectorial,":[32],"fixed-size":[33],"representation":[34],"the":[36,62,75,96,109,184],"MTS":[37,51,92,146,171,188],"that":[38,192],"can":[39],"be":[40],"further":[41],"processed":[42],"by":[43],"standard":[44,56],"classifiers.":[45],"Despite":[46],"their":[47],"unrivaled":[48],"training":[49],"speed,":[50],"classifiers":[52,194],"based":[53,82],"on":[54,83,183],"RC":[57,84,115,143,163,193],"architecture":[58],"fail":[59],"achieve":[61,206],"same":[63],"accuracy":[64],"fully":[66],"trainable":[67],"neural":[68],"networks.":[69],"In":[70],"this":[71],"article,":[72],"we":[73,139],"introduce":[74],"reservoir":[76,110],"model":[77,101,118],"space,":[78],"an":[79,130,149],"unsupervised":[80],"approach":[81],"learn":[86],"vectorial":[87],"representations":[88,122],"MTS.":[90],"Each":[91],"is":[93],"encoded":[94],"within":[95],"parameters":[97],"linear":[100],"trained":[102],"predict":[104],"low-dimensional":[106],"embedding":[107],"dynamics.":[111],"Compared":[112],"other":[114,170],"methods,":[116],"our":[117,202],"space":[119],"yields":[120],"better":[121],"attains":[124],"comparable":[125],"computational":[126],"performance":[127],"due":[128],"intermediate":[131],"dimensionality":[132],"reduction":[133],"procedure.":[134],"As":[135],"second":[137],"contribution,":[138],"propose":[140],"modular":[142],"framework":[144,155],"for":[145],"classification,":[147],"associated":[150],"open-source":[151],"Python":[152],"library.":[153],"The":[154,165],"different":[157],"modules":[158],"seamlessly":[160],"implement":[161],"advanced":[162],"architectures.":[164],"architectures":[166],"are":[167,195],"compared":[168],"classifiers,":[172],"including":[173],"deep":[174],"learning":[175],"models":[176],"kernels.":[180],"Results":[181],"obtained":[182],"benchmark":[185],"real-world":[187],"data":[189],"sets":[190],"show":[191],"dramatically":[196],"faster":[197],"and,":[198],"when":[199],"implemented":[200],"using":[201],"proposed":[203],"representation,":[204],"also":[205],"superior":[207],"classification":[208],"accuracy.":[209]},"counts_by_year":[{"year":2026,"cited_by_count":19},{"year":2025,"cited_by_count":58},{"year":2024,"cited_by_count":39},{"year":2023,"cited_by_count":33},{"year":2022,"cited_by_count":33},{"year":2021,"cited_by_count":23},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-18T07:39:51.176621","created_date":"2020-07-10T00:00:00"}
