論文筆記：Edge-Labeling Graph Neural Network for Few shot Learning
來源：paper, code，CVPR 2019, 韓國高等科技研究所&蒙特利爾大學 Abstract EGNN: edge-labeling graph neutral network 學習預測邊的label，使得網絡可以利用對於類內相似性和類間不相似性的直接連接狀態的探索，通過迭代更新邊的標籤，使得聚類表示是可以進化的 適合在各種數量的類別之間遷移並且不需要重新訓練 Introduction
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相關文章
- 1. 論文筆記--Edge-Labeling Graph Neural Network for Few-shot Learning--CVPR2019
- 2. 論文閱讀筆記《Edge-Labeling Graph Neural Network for Few-shot Learning》
- 3. FEW-SHOT LEARNING WITH GRAPH NEURAL NETWORK
- 4. 粗讀CVPR2019論文 Edge-Labeling Graph Neural Network for Few-shot Learning
- 5. 論文閱讀筆記《DPGN: Distribution Propagation Graph Network for Few-shot Learning》
- 6. Few-Shot Learning with Graph Neural Networks
- 7. 論文閱讀筆記《Few-Shot Learning with Graph Neural Networks》
- 8. Few-Shot Learning with Graph Neural Networks筆記
- 9. Few-shot Learning with Graph Neural Networks
- 10. 論文筆記：Prototypical Networks for Few-shot Learning