Strategies For Pre-Training Graph Neural Networks

时间 2021-01-02

标签图神经网络深度学习繁體版

原文原文链接

Paper : STRATEGIES FOR PRE-TRAINING GRAPH NEURAL NETWORKS Code : official 摘要作者解决的问题是如何预训练一个GNN网络，保证预训练的结果在具体数据集中finetune不会negative transfer 的现象。作者在文中并没有细致的解释为什么GNN上进行transfer learning 会更难，这个可能需要翻一下该篇

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1. STRATEGIES FOR PRE-TRAINING GRAPH NEURAL NETWORKS
2. 阅读笔记-STRATEGIES FOR PRE-TRAINING GRAPH NEURAL NETWORKS
3. Hybrid Graph Neural Networks for Crowd Counting
4. Graph Neural Networks for Social Recommendation
5. 阅读笔记--CAN GRAPH NEURAL NETWORKS GO “ONLINE”? AN ANALYSIS OF PRETRAINING AND INFERENCE
6. 深度图卷积网络系列文章（一）---Effective Training Strategies for Deep Graph Neural Networks
7. 【论文解读 ICLR 2020 | 图上的预训练】STRATEGIES FOR PRE-TRAINING GRAPH NEURAL NETWORKS
8. Applications of Graph Neural Networks
9. CS224W-08-Graph Neural Networks
10. Heterogeneous Graph Neural Networks for Extractive Document Summarization

>>更多相关文章<<