Investigating Transfer Learning in Graph Neural Networks

Graph neural networks (GNNs) build on the success of deep learning models by extending them for use in graph spaces. Transfer learning has proven extremely successful for traditional deep learning problems, resulting in faster training and improved performance. Despite the increasing interest in GNN...

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Autors principals: Nishai Kooverjee, Steven James, Terence van Zyl
Format: Artigo
Idioma:Inglês
Publicat: MDPI AG 2022-04-01
Col·lecció:Electronics
Matèries:
graph neural networks
machine learning
transfer learning
multi-task learning
Accés en línia:https://www.mdpi.com/2079-9292/11/8/1202
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