论文笔记:Few-Shot Lear With Graph Neural Networks
论文链接:Few shot learning with graph neural networks github代码链接:pytorch实现 1,INTRODUCTIION 1,元学习(新的监督学习):它的输入-输出对设置由图像集合的iid样本及其相关标签相似性代替了图像的iid样本和它相关标签. 2,探索利用相似样本的分布 代替 利用正则化取弥补数据的不足 3.文章贡献:
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相关文章
- 1. 笔记《Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels》-NeurIPS 2019
- 2. [2018][ICLR]FEW-SHOT LEARNING WITH GRAPH NEURAL NETWORKS 论文笔记
- 3. SuperGlue: Learning Feature Matching with Graph Neural Networks 2019 论文笔记
- 4. 论文阅读笔记《Few-Shot Learning with Graph Neural Networks》
- 5. FEW-SHOT LEARNING WITH GRAPH NEURAL NETWORKS 论文笔记
- 6. 【论文笔记】Learning Multi-view Camera Relocalization with Graph Neural Networks（CVPR2020）
- 7. Skeleton-Based Action Recognition with Directed Graph Neural Networks---论文笔记
- 8. GRNet: Learning Multi-view Camera Relocalization with Graph Neural Networks CVPR 2020 论文笔记
- 9. Few-Shot Learning with Graph Neural Networks笔记
- 10. 论文笔记：Exploring Neural Networks with Activation Atlases