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Learning in deep neural networks and brains with similarity-weighted interleaved learning

Proceedings of the National Academy of Sciences(2022)10.1073/pnas.2115229119Source: DataRank Database

Learning in deep neural networks and brains with similarity-weighted interleaved learning is a research paper published in Proceedings of the National Academy of Sciences (2022). On theSindex it has a DataRank of 0. It has been cited 16 times.

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0DataRank · unranked

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Open Access16 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (4 grants)OA: greenTopics (11)IDs (PubMed, PMC)

FAIR Checklist

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Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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Authors (3)

Justin L. Shobe ORCID,Bruce L. McNaughton ORCID,Rajat Saxena ORCID

Live enrichment

PubMed:35759669 PMC:PMC9271163

DOD | Defense Advanced Research Projects Agency

Grant: HR0011-18-2-0021

HHS | National Institutes of Health

Grant: NS12176401

NINDS NIH HHS

Grant: RF1 NS121764

NINDS NIH HHS

Grant: R01 NS121764

greenLicense: cc-by-nc-nd

repositoryhttps://escholarship.org/uc/item/1rw1b1m4

publisherhttps://pnas.org/doi/pdf/10.1073/pnas.2115229119

repositoryhttps://www.ncbi.nlm.nih.gov/pmc/articles/9271163

Europe_PMChttps://europepmc.org/articles/PMC9271163

Europe_PMChttps://europepmc.org/articles/PMC9271163?pdf=render

MeSH Terms

NeocortexHumansLearningModels, NeurologicalSystems TheoryNeural Networks, Computer

Keywords

MemoryLearningNeural networksMemory ConsolidationComplementary Learning Systems

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