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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...

詳細記述

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書誌詳細
主要な著者: Nishai Kooverjee, Steven James, Terence van Zyl
フォーマット: Artigo
言語:Inglês
出版事項: MDPI AG 2022-04-01
シリーズ:Electronics
主題:
オンライン・アクセス:https://www.mdpi.com/2079-9292/11/8/1202
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