元学习少样本图分类论文精选：近两年最新研究

以下是近两年基于元学习进行少样本图分类问题的论文：

1. 'Meta-learning for few-shot learning: A survey' by Yuxuan Wang, Devi Parikh, and Dhruv Batra (2021)

2. 'Few-shot learning with graph neural networks' by Zonghan Wu, Shirui Pan, Fengwen Chen, Guodong Long, Chengqi Zhang, and Philip S. Yu (2020)

3. 'Meta-learning with differentiable closed-form solvers' by Lu Yu, Tian Han, Tiancheng Shen, and Zhi-Hua Zhou (2021)

4. 'Learning to learn with conditional class dependencies' by Xingyu Chen, Yuxin Peng, Yali Du, and Yan Liu (2019)

5. 'Meta-learning neural networks for few-shot classification' by Sachin Ravi and Hugo Larochelle (2019)

6. 'Meta-learning with differentiable convex optimization' by Tian Han, Lu Yu, Tiancheng Shen, and Zhi-Hua Zhou (2020)

7. 'Efficient meta-learning for few-shot image classification' by Xu Chen, Tianbo Liu, Yinpeng Dong, Xiaoyu Liu, and Chen Change Loy (2020)

8. 'Meta-learning for few-shot image classification via learnable representations' by Hsin-Ying Lee, Jia-Bin Huang, Maneesh Kumar Singh, and Ming-Hsuan Yang (2020)

9. 'Few-shot learning via embeddings from randomized transformations' by Hongguang Zhang, Yuxiang Zhang, and Jia Li (2019)

10. 'Meta-learning with dynamic few-shot learning' by Yaqing Wang, Xin Li, Lei Che, and Wenwu Zhu (2020)