{"id":"https://openalex.org/W3131469407","doi":"https://doi.org/10.1109/ijcnn52387.2021.9534193","title":"One-shot learning for the long term: consolidation with an artificial hippocampal algorithm","display_name":"One-shot learning for the long term: consolidation with an artificial hippocampal algorithm","publication_year":2021,"publication_date":"2021-07-18","ids":{"openalex":"https://openalex.org/W3131469407","doi":"https://doi.org/10.1109/ijcnn52387.2021.9534193","mag":"3131469407"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn52387.2021.9534193","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9534193","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2102.07503","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5029075564","display_name":"Gideon Kowadlo","orcid":"https://orcid.org/0000-0001-6036-1180"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gideon Kowadlo","raw_affiliation_strings":["Cerenaut, Melbourne, Australia","Cerenaut,Melbourne,Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cerenaut, Melbourne, Australia","institution_ids":[]},{"raw_affiliation_string":"Cerenaut,Melbourne,Australia","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102008271","display_name":"Abdelrahman Ahmed","orcid":"https://orcid.org/0000-0001-9530-766X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Abdelrahman Ahmed","raw_affiliation_strings":["Cerenaut, Melbourne, Australia","Cerenaut,Melbourne,Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cerenaut, Melbourne, Australia","institution_ids":[]},{"raw_affiliation_string":"Cerenaut,Melbourne,Australia","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055640606","display_name":"David Rawlinson","orcid":"https://orcid.org/0000-0001-9443-3840"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"David Rawlinson","raw_affiliation_strings":["Cerenaut, Melbourne, Australia","Cerenaut,Melbourne,Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cerenaut, Melbourne, Australia","institution_ids":[]},{"raw_affiliation_string":"Cerenaut,Melbourne,Australia","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"2013","issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9993000030517578,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9993000030517578,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9898999929428101,"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/T10918","display_name":"Memory Processes and Influences","score":0.9891999959945679,"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/forgetting","display_name":"Forgetting","score":0.8927399516105652},{"id":"https://openalex.org/keywords/shot","display_name":"Shot (pellet)","score":0.6603732109069824},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.650093138217926},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6021552681922913},{"id":"https://openalex.org/keywords/neocortex","display_name":"Neocortex","score":0.5816349387168884},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.5356833934783936},{"id":"https://openalex.org/keywords/consolidation","display_name":"Consolidation (business)","score":0.44964325428009033},{"id":"https://openalex.org/keywords/memory-consolidation","display_name":"Memory consolidation","score":0.43886035680770874},{"id":"https://openalex.org/keywords/one-shot","display_name":"One shot","score":0.41738301515579224},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.411987841129303},{"id":"https://openalex.org/keywords/hippocampus","display_name":"Hippocampus","score":0.2969599962234497},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.20182061195373535},{"id":"https://openalex.org/keywords/cognitive-psychology","display_name":"Cognitive psychology","score":0.14965060353279114},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.12631872296333313},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09759882092475891}],"concepts":[{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.8927399516105652},{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.6603732109069824},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.650093138217926},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6021552681922913},{"id":"https://openalex.org/C2777222312","wikidata":"https://www.wikidata.org/wiki/Q726562","display_name":"Neocortex","level":2,"score":0.5816349387168884},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.5356833934783936},{"id":"https://openalex.org/C2776014549","wikidata":"https://www.wikidata.org/wiki/Q3050847","display_name":"Consolidation (business)","level":2,"score":0.44964325428009033},{"id":"https://openalex.org/C48455012","wikidata":"https://www.wikidata.org/wiki/Q2892593","display_name":"Memory consolidation","level":3,"score":0.43886035680770874},{"id":"https://openalex.org/C2992734406","wikidata":"https://www.wikidata.org/wiki/Q413267","display_name":"One shot","level":2,"score":0.41738301515579224},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.411987841129303},{"id":"https://openalex.org/C2781161787","wikidata":"https://www.wikidata.org/wiki/Q48360","display_name":"Hippocampus","level":2,"score":0.2969599962234497},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.20182061195373535},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.14965060353279114},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.12631872296333313},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09759882092475891},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/ijcnn52387.2021.9534193","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9534193","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2102.07503","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2102.07503","pdf_url":"https://arxiv.org/pdf/2102.07503","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:3131469407","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2102.07503","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2102.07503","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2102.07503","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2102.07503","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2102.07503","pdf_url":"https://arxiv.org/pdf/2102.07503","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.6399999856948853,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3131469407.pdf","grobid_xml":"https://content.openalex.org/works/W3131469407.grobid-xml"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W1531103298","https://openalex.org/W1853900790","https://openalex.org/W1970554717","https://openalex.org/W2016454630","https://openalex.org/W2022223337","https://openalex.org/W2049694336","https://openalex.org/W2100377190","https://openalex.org/W2159345153","https://openalex.org/W2194321275","https://openalex.org/W2194775991","https://openalex.org/W2401823607","https://openalex.org/W2424347275","https://openalex.org/W2549355627","https://openalex.org/W2601450892","https://openalex.org/W2798836702","https://openalex.org/W2804901184","https://openalex.org/W2938321354","https://openalex.org/W2961719374","https://openalex.org/W2962884963","https://openalex.org/W2963078860","https://openalex.org/W2963341924","https://openalex.org/W2963559848","https://openalex.org/W2963845150","https://openalex.org/W2973350090","https://openalex.org/W2974317861","https://openalex.org/W3019510943","https://openalex.org/W3030364939","https://openalex.org/W3091905774","https://openalex.org/W3106393803","https://openalex.org/W3108275947","https://openalex.org/W3137555817","https://openalex.org/W6631708475","https://openalex.org/W6638896900","https://openalex.org/W6713057566","https://openalex.org/W6717697761","https://openalex.org/W6735236233","https://openalex.org/W6738602802","https://openalex.org/W6776498132","https://openalex.org/W6783596713"],"related_works":["https://openalex.org/W2963026770","https://openalex.org/W2963038864","https://openalex.org/W2737492962","https://openalex.org/W3046808012","https://openalex.org/W3090333885","https://openalex.org/W2787295326","https://openalex.org/W3158218720","https://openalex.org/W113579815","https://openalex.org/W2564752792","https://openalex.org/W2990738692","https://openalex.org/W3166843586","https://openalex.org/W1502359229","https://openalex.org/W3101676467","https://openalex.org/W2985086263","https://openalex.org/W3106212374","https://openalex.org/W3003366625","https://openalex.org/W3021233013","https://openalex.org/W3040182061","https://openalex.org/W1982315076","https://openalex.org/W2754791538"],"abstract_inverted_index":{"Standard":[0],"few-shot":[1,15,147],"experiments":[2],"involve":[3],"learning":[4,16,47,91],"to":[5,38,52,85,88,138],"efficiently":[6],"match":[7],"unseen":[8],"samples":[9],"by":[10,46],"class.":[11],"We":[12],"claim":[13],"that":[14,81,100],"should":[17],"be":[18,72],"long":[19,95,118],"term,":[20],"assimilating":[21],"knowledge":[22,51,115],"for":[23,116],"the":[24,31,34,53,86,102,106,114,117,128],"future,":[25],"without":[26,120],"forgetting":[27],"previous":[28],"concepts.":[29],"In":[30,60],"mammalian":[32],"brain,":[33],"hippocampus":[35,137],"is":[36,125],"understood":[37],"play":[39],"a":[40,57,75,133,144],"significant":[41],"role":[42],"in":[43,110],"this":[44,61],"process,":[45],"rapidly":[48],"and":[49,94,112,141],"consolidating":[50],"neocortex":[54],"incrementally":[55,83],"over":[56],"short":[58,93],"period.":[59],"research":[62],"we":[63],"tested":[64],"whether":[65],"an":[66],"artificial":[67],"hippocampal":[68],"algorithm":[69],"(AHA),":[70],"could":[71,108],"used":[73],"with":[74,101],"conventional":[76],"Machine":[77],"Learning":[78],"(ML)":[79],"model":[80,135],"learns":[82],"analogous":[84],"neocortex,":[87],"achieve":[89],"one-shot":[90,111],"both":[92],"term.":[96],"The":[97],"results":[98],"demonstrated":[99],"addition":[103],"of":[104,127,131,136],"AHA,":[105],"system":[107],"learn":[109],"consolidate":[113,139],"term":[119],"catastrophic":[121],"forgetting.":[122],"This":[123],"study":[124],"one":[126],"first":[129],"examples":[130],"using":[132],"CLS":[134],"memories,":[140],"it":[142],"constitutes":[143],"step":[145],"toward":[146],"continual":[148],"learning.":[149]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2022-07-25T00:00:00"}
