其次 , 使用自监督目标对 GNN 模型进行预训练通常有利于最终模型的性能 。它可以增加训练示例的数量 , 有时还可以减少固有噪声 。
第三 , 为前置和最终预测任务测试不同的架构可以提高模型的预测能力 。
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Clement Gastaud Theophile Carniel and Jean-Michel Dalle. The varying importance of extrinsic factors in the success of startup fundraising: competition at early-stage and networks at growth-stage 2019.
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https://www.overfit.cn/post/bfaf84ba0c204ad08689016a79130dd5
【运营商|可以改善图神经网络,提升GNN性能的三个技巧】作者:Carlo H
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