Graph convolutional and attention models for entity classification in multilayer networks

Abstract Graph Neural Networks (GNNs) are powerful tools that are nowadays reaching state of the art performances in a plethora of different tasks such as node classification, link prediction and graph classification. A challenging aspect in this context is to redefine basic deep learning operations...

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Autores principales: Lorenzo Zangari, Roberto Interdonato, Antonio Calió, Andrea Tagarelli
Formato: article
Lenguaje:EN
Publicado: SpringerOpen 2021
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Acceso en línea:https://doaj.org/article/d1bb34a33b554382b426d19c23350495
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