[38] B. Xu, H. Shen, Q. Cao, Y. Qiu, and X. Cheng. Graph wavelet neural network. In International Conference on Learning Representations, 2019. [39] R. Ying, R. He, K. Chen, P. Eksombatchai, W. L. Hamilton, and J. Leskovec. Graph convolutional neural networks for web-scale ...
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Graph Wavelet Neural Network. Bingbing Xu, Huawei Shen, Qi Cao, Yunqi Qiu, Xueqi Cheng. ICLR, 2019. [Paper] Requirements The codebase is implemented in Python 3.5.2. package versions used for development are just below. networkx 2.4 tqdm 4.28.1 numpy 1.15.4 pandas 0.23.4 texttable 1.5....
Graph Wavelet Neural Network Bingbing Xu, Huawei Shen, Qi Cao, Yunqi Qiu, Xueqi Cheng ICLR 2019 Supervised Community Detection with Line Graph Neural Networks Zhengdao Chen, Xiang Li, Joan Bruna ICLR 2019 Predict then Propagate: Graph Neural Networks meet Personalized PageRank Johannes Klicpera, ...
GraphWave[2018]: Learning Structural Node Embeddings via Diffusion Wavelets 模型特点: 完全非监督,不需要任何先验知识。对比以往的模型,大多需要一些先验,比如struc2vec的先验是一个节点的局部性可以由其邻居的度序列表示(关于struc2vec,以及其他主流GE方法,这篇文章有详细介绍);然而GraphWave只需要输入拉普拉斯矩阵...
GraphWave[2018]: Learning Structural Node Embeddings via Diffusion Wavelets 模型特点: 完全非监督,不需要任何先验知识。对比以往的模型,大多需要一些先验,比如struc2vec的先验是一个节点的局部性可以由其邻居的度序列表示(关于struc2vec,以及其他主流GE方法,这篇文章有详细介绍);然而GraphWave只需要输入拉普拉斯矩阵...
Graph Neural Network(GNN)综述 导言 图(graph)是一个非常常用的数据结构,现实世界中很多很多任务可以描述为图问题,比如社交网络,蛋白体结构,交通路网数据,以及很火的知识图谱等,甚至规则网格结构数据(如图像,视频等)也是图数据的一种特殊形式,因此图是一个很值得研究的领域。
在第二代GCN中, 是 的矩阵,所以 的计算复杂度还是 ,论文Wavelets on graph via special graph theory提出了利用切比雪夫Chebyshev多项式拟合上文卷积核的方法,来降低计算复杂度。卷积核可以利用截断(truncated)的shifted Chebyshev多项式来近似逼近。 其中, : (经的最大特征值(即谱半径)缩放后的特征向量矩阵)的Cheby...
To the best of our knowledge, this paper is the first comprehensive survey that explores the application of graph neural networks for traffic forecasting problems. We have also created a public GitHub repository where the latest papers, open data, and source codes will be updated....
Graph Wavelet Neural Network. Bingbing Xu, Huawei Shen, Qi Cao, Yunqi Qiu, Xueqi Cheng. ICLR, 2019.pdf Overview We provide a TensorFlow implementation of Graph Wavelet Neural Network, which implements graph convolution via graph wavelet transform instead of Fourier transform. Different from graph ...