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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Egile Nagusiak: Nishai Kooverjee, Steven James, Terence van Zyl
Formatua: Artigo
Hizkuntza:Inglês
Argitaratua: MDPI AG 2022-04-01
Saila:Electronics
Gaiak:
graph neural networks
machine learning
transfer learning
multi-task learning
Sarrera elektronikoa:https://www.mdpi.com/2079-9292/11/8/1202
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