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 |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
SpringerOpen
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/d1bb34a33b554382b426d19c23350495 |
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