提交 49f28bab 编写于 作者: Y Yelrose

Update README.md

上级 01ee517f
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- We add newly graph level operators like **GraphPooling** and [**GraphNormalization**](https://arxiv.org/abs/2003.00982) for graph level predictions. - We add newly graph level operators like **GraphPooling** and [**GraphNormalization**](https://arxiv.org/abs/2003.00982) for graph level predictions.
- We relase a PGL-KE toolkit [here](./exmaples/pgl-ke) including classical knowledge graph algorithms like TransE, TransR, RotatE. - We relase a PGL-KE toolkit [here](./exmaples/pgl-ke) including classical knowledge graph embedding t algorithms like TransE, TransR, RotatE.
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- 新增了图级别的算子包括**GraphPooling**以及[**GraphNormalization**](https://arxiv.org/abs/2003.00982),这样你就能实现更多复杂的图级别分类模型。 - 新增了图级别的算子包括**GraphPooling**以及[**GraphNormalization**](https://arxiv.org/abs/2003.00982),这样你就能实现更多复杂的图级别分类模型。
- 新增PGL-KE工具包,里面包含许多经典知识图谱图嵌入算法,包括TransE, TransR, RotatE,详情可见[这里](./examples/pgl-ke)
Paddle Graph Learning (PGL)是一个基于[PaddlePaddle](https://github.com/PaddlePaddle/Paddle)的高效易用的图学习框架 Paddle Graph Learning (PGL)是一个基于[PaddlePaddle](https://github.com/PaddlePaddle/Paddle)的高效易用的图学习框架
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