Pre-Training Graph Neural Networks for Generic Structural Feature Extraction
Paper : Pre-Training Graph Neural Networks for Generic Structural Feature Extraction Code : 摘要 作者想要解決的任務是根據圖結構進行預測，通過構造三種與圖結構相關的損失函數——去噪連接重建、中心得分排名、集羣，作者給出的預訓練算法得到的模型參數可以包含從圖的局部到全局不同層次的結構信息。由於沒有標籤的要求，
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相關文章
- 1. Structural Image Classification with Graph Neural Networks
- 2. Applications of Graph Neural Networks
- 3. STRATEGIES FOR PRE-TRAINING GRAPH NEURAL NETWORKS
- 4. Strategies For Pre-Training Graph Neural Networks
- 5. Distant Supervision for Relation Extraction via Piecewise Convolutional Neural Networks
- 6. Hybrid Graph Neural Networks for Crowd Counting
- 7. Graph Neural Networks for Social Recommendation
- 8. Structural Design of Convolutional Neural Networks for Steganalysis
- 9. NR-SIQA Using Convolutional Neural Network for Adaptive Feature Extraction
- 10. Label-dependent Feature Extraction in Social Networks for Node Classification