论文浅尝 | GMNN: Graph Markov Neural Networks
论文笔记整理：吴锐，东南大学硕士研究生，研究方向为自然语言处理 来源：ICML 2019 链接：http://proceedings.mlr.press/v97/qu19a/qu19a.pdf 问题定义 弱监督下的在关系数据中的对象分类。形式化地来说，给定一个图G，图上有结点V表示一系列对象，在对象间存在有一系列边E，且每个结点都有对应的属性XV。当前已知部分结点L的标签，目的
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相关文章
- 1. GMNN: Graph Markov Neural Networks
- 2. 论文浅尝 | GEOM-GCN: Geometric Graph Convolutional Networks
- 3. CS224W-08-Graph Neural Networks
- 4. Applications of Graph Neural Networks
- 5. 论文浅尝 | Open world Knowledge Graph Completion
- 6. 论文浅尝 | Improved Neural Relation Detection for KBQA
- 7. 论文浅尝 | CFO: Conditional Focused Neural Question Answering
- 8. Adaptive Graph Convolutional Neural Networks
- 9. Towards Deeper Graph Neural Networks
- 10. 笔记《Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels》-NeurIPS 2019