{"id":"https://openalex.org/W2521529690","doi":"https://doi.org/10.1109/ssp.2018.8450698","title":"Scaling Up Echo-State Networks With Multiple Light Scattering","display_name":"Scaling Up Echo-State Networks With Multiple Light Scattering","publication_year":2018,"publication_date":"2018-06-01","ids":{"openalex":"https://openalex.org/W2521529690","doi":"https://doi.org/10.1109/ssp.2018.8450698","mag":"2521529690"},"language":"en","primary_location":{"id":"doi:10.1109/ssp.2018.8450698","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssp.2018.8450698","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Statistical Signal Processing Workshop (SSP)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1609.05204","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Jonathan Dong","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Jonathan Dong","raw_affiliation_strings":["LightOn, 2 rue de la Bourse, Paris, France"],"affiliations":[{"raw_affiliation_string":"LightOn, 2 rue de la Bourse, Paris, France","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Sylvain Gigan","orcid":null},"institutions":[{"id":"https://openalex.org/I2801195679","display_name":"Laboratoire Kastler Brossel","ror":"https://ror.org/01h14ww21","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I187986737","https://openalex.org/I2746051580","https://openalex.org/I2801195679","https://openalex.org/I29607241","https://openalex.org/I39804081","https://openalex.org/I4210098836"]},{"id":"https://openalex.org/I39804081","display_name":"Sorbonne Universit\u00e9","ror":"https://ror.org/02en5vm52","country_code":"FR","type":"education","lineage":["https://openalex.org/I39804081"]},{"id":"https://openalex.org/I29607241","display_name":"\u00c9cole Normale Sup\u00e9rieure - PSL","ror":"https://ror.org/05a0dhs15","country_code":"FR","type":"funder","lineage":["https://openalex.org/I2746051580","https://openalex.org/I29607241"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"funder","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I2746051580","display_name":"Universit\u00e9 Paris Sciences et Lettres","ror":"https://ror.org/013cjyk83","country_code":"FR","type":"education","lineage":["https://openalex.org/I2746051580"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Sylvain Gigan","raw_affiliation_strings":["Laboratoire Kastler Brossel, CNRS UMR 8552, \u00c9cole Normale Sup\u00e9rieure, PSL Research University, Sorbonne Universit\u00e9s & Universit\u00e9 Pierre et Marie Curie, Paris, France"],"affiliations":[{"raw_affiliation_string":"Laboratoire Kastler Brossel, CNRS UMR 8552, \u00c9cole Normale Sup\u00e9rieure, PSL Research University, Sorbonne Universit\u00e9s & Universit\u00e9 Pierre et Marie Curie, Paris, France","institution_ids":["https://openalex.org/I2801195679","https://openalex.org/I39804081","https://openalex.org/I29607241","https://openalex.org/I2746051580","https://openalex.org/I1294671590"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Florent Krzakala","orcid":null},"institutions":[{"id":"https://openalex.org/I2746051580","display_name":"Universit\u00e9 Paris Sciences et Lettres","ror":"https://ror.org/013cjyk83","country_code":"FR","type":"education","lineage":["https://openalex.org/I2746051580"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"funder","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I39804081","display_name":"Sorbonne Universit\u00e9","ror":"https://ror.org/02en5vm52","country_code":"FR","type":"education","lineage":["https://openalex.org/I39804081"]},{"id":"https://openalex.org/I29607241","display_name":"\u00c9cole Normale Sup\u00e9rieure - PSL","ror":"https://ror.org/05a0dhs15","country_code":"FR","type":"funder","lineage":["https://openalex.org/I2746051580","https://openalex.org/I29607241"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Florent Krzakala","raw_affiliation_strings":["Laboratoire de Physique Statistique, CNRS, \u00c9cole Normale Sup\u00e9rieure, PSL Research University, Sorbonne Universit\u00e9s et Universit\u00e9 Pierre & Marie Curie, Paris, France"],"affiliations":[{"raw_affiliation_string":"Laboratoire de Physique Statistique, CNRS, \u00c9cole Normale Sup\u00e9rieure, PSL Research University, Sorbonne Universit\u00e9s et Universit\u00e9 Pierre & Marie Curie, Paris, France","institution_ids":["https://openalex.org/I39804081","https://openalex.org/I29607241","https://openalex.org/I2746051580","https://openalex.org/I1294671590"]}]},{"author_position":"last","author":{"id":null,"display_name":"Gilles Wainrib","orcid":null},"institutions":[{"id":"https://openalex.org/I29607241","display_name":"\u00c9cole Normale Sup\u00e9rieure - PSL","ror":"https://ror.org/05a0dhs15","country_code":"FR","type":"funder","lineage":["https://openalex.org/I2746051580","https://openalex.org/I29607241"]},{"id":"https://openalex.org/I4210161954","display_name":"D\u00e9partement d'Informatique","ror":"https://ror.org/05y6rqs46","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I1326498283","https://openalex.org/I2746051580","https://openalex.org/I29607241","https://openalex.org/I4210159245","https://openalex.org/I4210161954"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Gilles Wainrib","raw_affiliation_strings":["D\u00e9partement d\u2019Informatique, \u00c9cole Normale Sup\u00e9rieure, Paris, France"],"affiliations":[{"raw_affiliation_string":"D\u00e9partement d\u2019Informatique, \u00c9cole Normale Sup\u00e9rieure, Paris, France","institution_ids":["https://openalex.org/I29607241","https://openalex.org/I4210161954"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0125,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.81716777,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"448","last_page":"452"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","score":1.0,"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":1.0,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9897000193595886,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11996","display_name":"Random lasers and scattering media","score":0.9864000082015991,"subfield":{"id":"https://openalex.org/subfields/3102","display_name":"Acoustics and Ultrasonics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.6144999861717224},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5888000130653381},{"id":"https://openalex.org/keywords/chaotic","display_name":"Chaotic","score":0.5726000070571899},{"id":"https://openalex.org/keywords/quadratic-growth","display_name":"Quadratic growth","score":0.5462999939918518},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5131000280380249},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.5073999762535095},{"id":"https://openalex.org/keywords/scattering","display_name":"Scattering","score":0.38760000467300415},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.38190001249313354}],"concepts":[{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.6144999861717224},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5888000130653381},{"id":"https://openalex.org/C2777052490","wikidata":"https://www.wikidata.org/wiki/Q5072826","display_name":"Chaotic","level":2,"score":0.5726000070571899},{"id":"https://openalex.org/C195956108","wikidata":"https://www.wikidata.org/wiki/Q7268362","display_name":"Quadratic growth","level":2,"score":0.5462999939918518},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5396999716758728},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5131000280380249},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.5073999762535095},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46939998865127563},{"id":"https://openalex.org/C191486275","wikidata":"https://www.wikidata.org/wiki/Q210028","display_name":"Scattering","level":2,"score":0.38760000467300415},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.38190001249313354},{"id":"https://openalex.org/C135796866","wikidata":"https://www.wikidata.org/wiki/Q7315328","display_name":"Reservoir computing","level":4,"score":0.37779998779296875},{"id":"https://openalex.org/C311688","wikidata":"https://www.wikidata.org/wiki/Q2393193","display_name":"Time complexity","level":2,"score":0.34709998965263367},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3287999927997589},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.32749998569488525},{"id":"https://openalex.org/C120456961","wikidata":"https://www.wikidata.org/wiki/Q210028","display_name":"Light scattering","level":3,"score":0.3190999925136566},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.31119999289512634},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.305400013923645},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.30090001225471497},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.30000001192092896},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2973000109195709},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.2924000024795532},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.2842000126838684},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.2802000045776367},{"id":"https://openalex.org/C170122806","wikidata":"https://www.wikidata.org/wiki/Q1914828","display_name":"Linear scale","level":2,"score":0.26829999685287476},{"id":"https://openalex.org/C129404179","wikidata":"https://www.wikidata.org/wiki/Q1469765","display_name":"Optical communication","level":2,"score":0.266400009393692},{"id":"https://openalex.org/C124978682","wikidata":"https://www.wikidata.org/wiki/Q1201019","display_name":"Proof of concept","level":2,"score":0.25119999051094055}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ssp.2018.8450698","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssp.2018.8450698","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Statistical Signal Processing Workshop (SSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1609.05204","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1609.05204","pdf_url":"https://arxiv.org/pdf/1609.05204","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1609.05204","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1609.05204","pdf_url":"https://arxiv.org/pdf/1609.05204","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1919767399","https://openalex.org/W1965702053","https://openalex.org/W1978718464","https://openalex.org/W1988016806","https://openalex.org/W2019236124","https://openalex.org/W2029939668","https://openalex.org/W2037024114","https://openalex.org/W2057755457","https://openalex.org/W2064507845","https://openalex.org/W2103179919","https://openalex.org/W2103869034","https://openalex.org/W2118706537","https://openalex.org/W2171865010","https://openalex.org/W2317647934","https://openalex.org/W6603161775","https://openalex.org/W6634876549","https://openalex.org/W6650267568","https://openalex.org/W6683501082","https://openalex.org/W6685384837","https://openalex.org/W6747722507","https://openalex.org/W6769341872"],"related_works":[],"abstract_inverted_index":{"Echo-State":[0,70],"Networks":[1,71],"and":[2,29,60,75,105],"Reservoir":[3],"Computing":[4],"have":[5,87],"been":[6,88],"studied":[7],"for":[8],"more":[9],"than":[10],"a":[11,15,65,76,81],"decade.":[12],"They":[13,37],"provide":[14],"simpler":[16],"yet":[17],"powerful":[18],"alternative":[19],"to":[20,50,91,108],"Recurrent":[21],"Neural":[22],"Networks,":[23],"every":[24],"internal":[25],"weight":[26],"is":[27,35,101],"fixed":[28],"only":[30],"the":[31,53,93],"last":[32],"linear":[33],"layer":[34],"trained.":[36],"involve":[38],"many":[39],"multiplications":[40],"by":[41],"dense":[42],"random":[43],"matrices.":[44],"Very":[45],"large":[46,110],"networks":[47,86],"are":[48],"difficult":[49],"obtain,":[51],"as":[52],"complexity":[54],"scales":[55],"quadratically":[56],"both":[57],"in":[58],"time":[59,96],"memory.":[61],"Here,":[62],"we":[63],"present":[64],"novel":[66],"optical":[67],"implementation":[68],"of":[69,83],"using":[72],"light-scattering":[73],"media":[74],"Digital":[77],"Micromirror":[78],"Device.":[79],"As":[80],"proof":[82],"concept,":[84],"binary":[85],"successfully":[89],"trained":[90],"predict":[92],"chaotic":[94],"Mackey-Glass":[95],"series.":[97],"This":[98],"new":[99],"method":[100],"fast,":[102],"power":[103],"efficient":[104],"easily":[106],"scalable":[107],"very":[109],"networks.":[111]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2}],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2016-09-30T00:00:00"}
