{"id":"https://openalex.org/W2597948870","doi":"https://doi.org/10.1109/tnnls.2017.2677968","title":"Recurrent Neural Networks With Auxiliary Memory Units","display_name":"Recurrent Neural Networks With Auxiliary Memory Units","publication_year":2017,"publication_date":"2017-03-22","ids":{"openalex":"https://openalex.org/W2597948870","doi":"https://doi.org/10.1109/tnnls.2017.2677968","mag":"2597948870","pmid":"https://pubmed.ncbi.nlm.nih.gov/28333646"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2017.2677968","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2017.2677968","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"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":"journal-article"},"type":"article","indexed_in":["crossref","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/A5100630871","display_name":"Jianyong Wang","orcid":"https://orcid.org/0000-0003-1689-2384"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jianyong Wang","raw_affiliation_strings":["Machine Intelligence Laboratory, College of Computer Science, Sichuan University, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Machine Intelligence Laboratory, College of Computer Science, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I4210125143","https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108970670","display_name":"Lei Zhang","orcid":"https://orcid.org/0000-0001-8795-5675"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Zhang","raw_affiliation_strings":["Machine Intelligence Laboratory, College of Computer Science, Sichuan University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-5867-9322","affiliations":[{"raw_affiliation_string":"Machine Intelligence Laboratory, College of Computer Science, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I4210125143","https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112307326","display_name":"Quan Guo","orcid":null},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Quan Guo","raw_affiliation_strings":["Machine Intelligence Laboratory, College of Computer Science, Sichuan University, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Machine Intelligence Laboratory, College of Computer Science, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I4210125143","https://openalex.org/I24185976"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100388188","display_name":"Yi Zhang","orcid":"https://orcid.org/0000-0002-5867-9322"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhang Yi","raw_affiliation_strings":["Machine Intelligence Laboratory, College of Computer Science, Sichuan University, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Machine Intelligence Laboratory, College of Computer Science, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I4210125143","https://openalex.org/I24185976"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100630871"],"corresponding_institution_ids":["https://openalex.org/I24185976","https://openalex.org/I4210125143"],"apc_list":null,"apc_paid":null,"fwci":6.6514,"has_fulltext":false,"cited_by_count":59,"citation_normalized_percentile":{"value":0.97236542,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"29","issue":"5","first_page":"1652","last_page":"1661"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9994999766349792,"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/T10320","display_name":"Neural Networks and Applications","score":0.9994999766349792,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9851999878883362,"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/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.983299970626831,"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/recurrent-neural-network","display_name":"Recurrent neural network","score":0.919036865234375},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7887952327728271},{"id":"https://openalex.org/keywords/sequence-learning","display_name":"Sequence learning","score":0.6476589441299438},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5070044994354248},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.5037400126457214},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4425268769264221},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.4387553632259369},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43677663803100586},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4155944883823395}],"concepts":[{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.919036865234375},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7887952327728271},{"id":"https://openalex.org/C40506919","wikidata":"https://www.wikidata.org/wiki/Q7452469","display_name":"Sequence learning","level":2,"score":0.6476589441299438},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5070044994354248},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.5037400126457214},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4425268769264221},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.4387553632259369},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43677663803100586},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4155944883823395},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"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/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2017.2677968","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2017.2677968","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"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":"journal-article"},{"id":"pmid:28333646","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/28333646","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":[{"id":"https://openalex.org/G7201487572","display_name":null,"funder_award_id":"61322203","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7670333304","display_name":null,"funder_award_id":"61432012","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W196214544","https://openalex.org/W1408639475","https://openalex.org/W1498436455","https://openalex.org/W1674799117","https://openalex.org/W1815076433","https://openalex.org/W1895577753","https://openalex.org/W1923211482","https://openalex.org/W1924770834","https://openalex.org/W1947481528","https://openalex.org/W2016589492","https://openalex.org/W2034797247","https://openalex.org/W2064675550","https://openalex.org/W2100471656","https://openalex.org/W2107878631","https://openalex.org/W2108563286","https://openalex.org/W2110485445","https://openalex.org/W2136848157","https://openalex.org/W2143612262","https://openalex.org/W2145581742","https://openalex.org/W2145634682","https://openalex.org/W2157331557","https://openalex.org/W2157479813","https://openalex.org/W2473934411","https://openalex.org/W2486697635","https://openalex.org/W2950635152","https://openalex.org/W3099884890","https://openalex.org/W4254816979","https://openalex.org/W4294555862","https://openalex.org/W6607974698","https://openalex.org/W6628131027","https://openalex.org/W6637157234","https://openalex.org/W6638545294","https://openalex.org/W6640212811","https://openalex.org/W6720905350"],"related_works":["https://openalex.org/W4298287631","https://openalex.org/W2953061907","https://openalex.org/W3008584592","https://openalex.org/W2883195674","https://openalex.org/W2072736607","https://openalex.org/W2597948870","https://openalex.org/W2428505524","https://openalex.org/W2962722950","https://openalex.org/W3080374445","https://openalex.org/W2964790801"],"abstract_inverted_index":{"Memory":[0],"is":[1,51,81,104],"one":[2],"of":[3,57,71,110,189,201,222],"the":[4,55,93,108,120,139,148,153,165,179,187,199,214,223,227,242,247],"most":[5],"important":[6],"mechanisms":[7],"in":[8,19,54,85,161,175,183,241,251],"recurrent":[9,163,185],"neural":[10],"networks":[11],"(RNNs)":[12],"learning.":[13,25,45],"It":[14],"plays":[15],"a":[16,27,47,62,86,131,158,162,184],"crucial":[17],"role":[18],"practical":[20],"applications,":[21],"such":[22],"as":[23],"sequence":[24,252,255],"With":[26],"good":[28,220],"memory":[29,49,64,78,94,129,154,170,174,180,207],"mechanism,":[30],"long":[31,132],"term":[32],"history":[33],"can":[34,41,124,192],"be":[35,193],"fused":[36],"with":[37,119,157,238],"current":[38],"information,":[39],"and":[40,95,98,126,143,155,181,226,245,254],"thus":[42],"improve":[43],"RNNs":[44],"Developing":[46],"suitable":[48],"mechanism":[50,65],"always":[52],"desirable":[53],"field":[56],"RNNs.":[58,67],"This":[59,135],"paper":[60,73],"proposes":[61],"novel":[63],"for":[66],"The":[68,114,217,231],"main":[69],"contributions":[70],"this":[72],"are:":[74],"1)":[75],"an":[76,100,168],"auxiliary":[77,169,206],"unit":[79],"(AMU)":[80],"proposed,":[82],"which":[83,151],"results":[84],"new":[87],"special":[88],"RNN":[89,249],"model":[90],"(AMU-RNN),":[91],"separating":[92,178],"output":[96,156,182],"explicitly":[97],"2)":[99],"efficient":[101,235],"learning":[102,122,140,190,215,229,236,244],"algorithm":[103],"developed":[105,121,228],"by":[106,197],"employing":[107],"technique":[109,200],"error":[111,202,211],"flow":[112,203,212],"truncation.":[113],"proposed":[115,224],"AMU-RNN":[116,243],"model,":[117],"together":[118],"algorithm,":[123],"learn":[125],"maintain":[127,173],"stable":[128,239],"over":[130],"time":[133],"range.":[134],"method":[136,232],"overcomes":[137],"both":[138],"conflict":[141],"problem":[142,188],"gradient":[144],"vanishing":[145],"problem.":[146],"Unlike":[147],"traditional":[149],"method,":[150],"mixes":[152],"single":[159],"neuron":[160,171,208],"unit,":[164,186],"AMU":[166],"provides":[167],"to":[172],"particular.":[176],"By":[177],"conflicts":[191],"eliminated":[194],"easily.":[195],"Moreover,":[196],"using":[198],"truncation,":[204],"each":[205],"ensures":[209],"constant":[210],"during":[213],"process.":[216],"experiments":[218],"demonstrate":[219],"performance":[221,237],"AMU-RNNs":[225],"algorithm.":[230],"exhibits":[233],"quite":[234],"convergence":[240],"outperforms":[246],"state-of-the-art":[248],"models":[250],"generation":[253],"classification":[256],"tasks.":[257]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":13},{"year":2019,"cited_by_count":13},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
