2025-02-21T08:11:14-05:00 DEBUG: VuFindSearch\Backend\Solr\Connector: Query fl=%2A&wt=json&json.nl=arrarr&q=id%3A%22journaliasakpiua-article-322523%22&qt=morelikethis&rows=5
2025-02-21T08:11:14-05:00 DEBUG: VuFindSearch\Backend\Solr\Connector: => GET http://localhost:8983/solr/biblio/select?fl=%2A&wt=json&json.nl=arrarr&q=id%3A%22journaliasakpiua-article-322523%22&qt=morelikethis&rows=5
2025-02-21T08:11:14-05:00 DEBUG: VuFindSearch\Backend\Solr\Connector: <= 200 OK
2025-02-21T08:11:14-05:00 DEBUG: Deserialized SOLR response
Про еволюцію рекурентних нейронних систем

Про еволюцію рекурентних нейронних систем

The evolution of neural network architectures, first of the recurrent type and then with the use of attention technology, is considered. It shows how the approaches changed and how the developers’ experience was enriched. It is important that the neural networks themselves learn to understand the de...

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Bibliographic Details
Main Authors: Abramov, Gennadii, Gushchin, Ivan, Sirenka, Tetiana
Format: Article
Language:English
Published: The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" 2024
Subjects:
рекурентні нейронні мережі
технологія трансформер
KAN
Online Access:http://journal.iasa.kpi.ua/article/view/322523
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2025-02-21T08:11:14-05:00 DEBUG: VuFindSearch\Backend\Solr\Connector: Query fl=%2A&rows=40&rows=5&wt=json&json.nl=arrarr&q=id%3A%22journaliasakpiua-article-322523%22&qt=morelikethis
2025-02-21T08:11:14-05:00 DEBUG: VuFindSearch\Backend\Solr\Connector: => GET http://localhost:8983/solr/biblio/select?fl=%2A&rows=40&rows=5&wt=json&json.nl=arrarr&q=id%3A%22journaliasakpiua-article-322523%22&qt=morelikethis
2025-02-21T08:11:14-05:00 DEBUG: VuFindSearch\Backend\Solr\Connector: <= 200 OK
2025-02-21T08:11:14-05:00 DEBUG: Deserialized SOLR response

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