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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Hlavní autoři: Nishai Kooverjee, Steven James, Terence van Zyl
Médium: Artigo
Jazyk:Inglês
Vydáno: MDPI AG 2022-04-01
Edice:Electronics
Témata:
graph neural networks
machine learning
transfer learning
multi-task learning
On-line přístup:https://www.mdpi.com/2079-9292/11/8/1202
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