{"id":"https://openalex.org/W3206862616","doi":"https://doi.org/10.1145/3477145.3477155","title":"Neko: a Library for Exploring Neuromorphic Learning Rules","display_name":"Neko: a Library for Exploring Neuromorphic Learning Rules","publication_year":2021,"publication_date":"2021-07-27","ids":{"openalex":"https://openalex.org/W3206862616","doi":"https://doi.org/10.1145/3477145.3477155","mag":"3206862616"},"language":"en","primary_location":{"id":"doi:10.1145/3477145.3477155","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3477145.3477155","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Conference on Neuromorphic Systems 2021","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"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/A5101737194","display_name":"Zixuan Zhao","orcid":"https://orcid.org/0000-0001-6934-0765"},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zixuan Zhao","raw_affiliation_strings":["The University of Chicago"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Chicago","institution_ids":["https://openalex.org/I40347166"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021501780","display_name":"Nathan Wycoff","orcid":"https://orcid.org/0000-0002-0336-7401"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nathan Wycoff","raw_affiliation_strings":["Virginia Tech"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Virginia Tech","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045490083","display_name":"Neil Getty","orcid":"https://orcid.org/0000-0003-0535-8362"},"institutions":[{"id":"https://openalex.org/I1282105669","display_name":"Argonne National Laboratory","ror":"https://ror.org/05gvnxz63","country_code":"US","type":"facility","lineage":["https://openalex.org/I1282105669","https://openalex.org/I1330989302","https://openalex.org/I39565521","https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Neil Getty","raw_affiliation_strings":["Argonne National Laboratory"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Argonne National Laboratory","institution_ids":["https://openalex.org/I1282105669"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053682943","display_name":"Rick Stevens","orcid":"https://orcid.org/0000-0002-4268-4020"},"institutions":[{"id":"https://openalex.org/I1282105669","display_name":"Argonne National Laboratory","ror":"https://ror.org/05gvnxz63","country_code":"US","type":"facility","lineage":["https://openalex.org/I1282105669","https://openalex.org/I1330989302","https://openalex.org/I39565521","https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rick Stevens","raw_affiliation_strings":["Argonne National Laboratory"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Argonne National Laboratory","institution_ids":["https://openalex.org/I1282105669"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049471852","display_name":"Fangfang Xia","orcid":"https://orcid.org/0000-0001-6567-0564"},"institutions":[{"id":"https://openalex.org/I1282105669","display_name":"Argonne National Laboratory","ror":"https://ror.org/05gvnxz63","country_code":"US","type":"facility","lineage":["https://openalex.org/I1282105669","https://openalex.org/I1330989302","https://openalex.org/I39565521","https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fangfang Xia","raw_affiliation_strings":["Argonne National Laboratory"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Argonne National Laboratory","institution_ids":["https://openalex.org/I1282105669"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.814,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.66016314,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":1.0,"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/T10581","display_name":"Neural dynamics and brain function","score":0.9979000091552734,"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"}},{"id":"https://openalex.org/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9979000091552734,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/python","display_name":"Python (programming language)","score":0.7929034233093262},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7924604415893555},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7048952579498291},{"id":"https://openalex.org/keywords/neuromorphic-engineering","display_name":"Neuromorphic engineering","score":0.6941421031951904},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5778143405914307},{"id":"https://openalex.org/keywords/modular-design","display_name":"Modular design","score":0.5630633234977722},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5162113308906555},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.49785733222961426},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.4829927682876587},{"id":"https://openalex.org/keywords/bridging","display_name":"Bridging (networking)","score":0.44595882296562195},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2638675570487976},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.12059286236763}],"concepts":[{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.7929034233093262},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7924604415893555},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7048952579498291},{"id":"https://openalex.org/C151927369","wikidata":"https://www.wikidata.org/wiki/Q1981312","display_name":"Neuromorphic engineering","level":3,"score":0.6941421031951904},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5778143405914307},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.5630633234977722},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5162113308906555},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.49785733222961426},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.4829927682876587},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.44595882296562195},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2638675570487976},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.12059286236763},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3477145.3477155","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3477145.3477155","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Conference on Neuromorphic Systems 2021","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4099999964237213,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1615659442","https://openalex.org/W1966288303","https://openalex.org/W2021383442","https://openalex.org/W2057291289","https://openalex.org/W2065125569","https://openalex.org/W2087861759","https://openalex.org/W2091777687","https://openalex.org/W2132003317","https://openalex.org/W2135973421","https://openalex.org/W2140886546","https://openalex.org/W2159543793","https://openalex.org/W2513853720","https://openalex.org/W2751543632","https://openalex.org/W2775079417","https://openalex.org/W2792794651","https://openalex.org/W2798651459","https://openalex.org/W2800613970","https://openalex.org/W2892242726","https://openalex.org/W2912265134","https://openalex.org/W2935958002","https://openalex.org/W2941300701","https://openalex.org/W2954040150","https://openalex.org/W2954713924","https://openalex.org/W2969331319","https://openalex.org/W2969774045","https://openalex.org/W2984844508","https://openalex.org/W2997466403","https://openalex.org/W3016391357","https://openalex.org/W3031127341","https://openalex.org/W3043133474","https://openalex.org/W3099743262","https://openalex.org/W3106455851","https://openalex.org/W3109872205","https://openalex.org/W3118540096","https://openalex.org/W3127686677","https://openalex.org/W3135825807","https://openalex.org/W3201524232","https://openalex.org/W4236503105","https://openalex.org/W4252930359","https://openalex.org/W4288287658","https://openalex.org/W6713134421"],"related_works":["https://openalex.org/W4386603768","https://openalex.org/W2950475743","https://openalex.org/W2886711096","https://openalex.org/W2750384547","https://openalex.org/W3137378424","https://openalex.org/W2809732489","https://openalex.org/W4287780255","https://openalex.org/W3023361272","https://openalex.org/W4391092513","https://openalex.org/W4393235919"],"abstract_inverted_index":{"The":[0],"field":[1],"of":[2,9,46,95,103],"neuromorphic":[3],"computing":[4],"is":[5,38,155],"in":[6,105,129,136],"a":[7,84,89],"period":[8],"active":[10],"exploration.":[11],"While":[12],"many":[13],"tools":[14,143],"have":[15],"been":[16],"developed":[17],"to":[18,26,41,48,58,69,133],"simulate":[19],"neuronal":[20],"dynamics":[21],"or":[22],"convert":[23],"deep":[24],"networks":[25],"spiking":[27],"models,":[28],"general":[29],"software":[30],"libraries":[31],"for":[32],"learning":[33,51,71,97],"rules":[34],"remain":[35],"underexplored.":[36],"This":[37],"partly":[39],"due":[40],"the":[42,66,93,101,125],"diverse,":[43],"challenging":[44],"nature":[45],"efforts":[47],"design":[49,94],"new":[50,96,151],"rules,":[52],"which":[53],"range":[54],"from":[55,61],"encoding":[56],"methods":[57],"gradient":[59,145],"approximations,":[60],"population":[62],"approaches":[63],"that":[64,121,147,161],"mimic":[65],"Bayesian":[67],"brain":[68],"constrained":[70],"algorithms":[72,127],"deployed":[73],"on":[74,91],"memristor":[75],"crossbars.":[76],"To":[77],"address":[78],"this":[79],"gap,":[80],"we":[81],"present":[82],"Neko,":[83],"modular,":[85],"extensible":[86],"library":[87,160],"with":[88],"focus":[90],"aiding":[92],"algorithms.":[98],"We":[99],"demonstrate":[100],"utility":[102],"Neko":[104,122,154],"three":[106],"exemplar":[107],"cases:":[108],"online":[109],"local":[110],"learning,":[111,113],"probabilistic":[112],"and":[114,138,164],"analog":[115],"on-device":[116],"learning.":[117],"Our":[118],"results":[119],"show":[120],"can":[123,148],"replicate":[124],"state-of-the-art":[126],"and,":[128],"one":[130],"case,":[131],"lead":[132],"significant":[134],"outperformance":[135],"accuracy":[137],"speed.":[139],"Further,":[140],"it":[141],"offers":[142],"including":[144],"comparison":[146],"help":[149],"develop":[150],"algorithmic":[152],"variants.":[153],"an":[156],"open":[157],"source":[158],"Python":[159],"supports":[162],"PyTorch":[163],"TensorFlow":[165],"backends.":[166]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-30T17:31:21.811387","created_date":"2025-10-10T00:00:00"}