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Combining aggregated attention and transformer architecture for accurate and efficient performance of Spiking Neural Networks

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dc.contributor.authorZhang, H.
dc.contributor.authorSboev, A.
dc.contributor.authorRybka, R.
dc.contributor.authorYu, Q.
dc.contributor.authorСбоев, Александр Георгиевич
dc.contributor.authorРыбка, Роман Борисович
dc.date.accessioned2025-09-25T14:19:34Z
dc.date.available2025-09-25T14:19:34Z
dc.date.issued2025
dc.identifier.citationCombining aggregated attention and transformer architecture for accurate and efficient performance of Spiking Neural Networks / Zhang, H. [et al.] // Neural Networks. - 2025. - 191. - 10.1016/j.neunet.2025.107789
dc.identifier.doi10.1016/j.neunet.2025.107789
dc.identifier.urihttps://www.doi.org/10.1016/j.neunet.2025.107789
dc.identifier.urihttps://www.scopus.com/record/display.uri?eid=2-s2.0-105009944685&origin=resultslist
dc.identifier.urihttps://openrepository.mephi.ru/handle/123456789/38428
dc.relation.ispartofNeural Networks
dc.titleCombining aggregated attention and transformer architecture for accurate and efficient performance of Spiking Neural Networks
dc.typeArticle
dspace.entity.typePublication
oaire.citation.volume191
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