Recently, graph wavelet neural network (GWNN) has made a significant improvement for this task. However, GWNN is usually shallow based on a one- or two-hop neighborhood structure, making it unable to obtain sufficient global information to make it better. But, if GWNN merely stacks too many ...
A TensorFlow implementation of Graph Wavelet Neural Network 图小波神经网络的TensorFlow实现 - waveletpytorch/GWNN
We present graph wavelet neural network (GWNN), a novel graph convolutional neural network (CNN), leveraging graph wavelet transform to address the shortcomings of previous spectral graph CNN methods that depend on graph Fourier transform. Different from graph Fourier transform, graph wavelet transform...
We present graph wavelet neural network (GWNN), a novel graph convolutional neural network (CNN), leveraging graph wavelet transform to address the shortcomings of previous spectral graph CNN methods that depend on graph Fourier transform. Different from graph Fourier transform, graph wavelet transform...
In addition to the semi-supervised GCN31, we also evaluate the other different graph neural network methods, including HYPERGCN54, GAT55, GWNN56, GraphSAGE57, and ChebyNet58, based on our constructed hybrid graph. GCN shows the best overall performance; HYPERGCN, GAT, and GWNN are also good ...
trainer = GWNNTrainer(args, sparsifier, features, target) trainer.fit() trainer.score() save_logs(args, trainer.logs) 开发者ID:benedekrozemberczki,项目名称:GraphWaveletNeuralNetwork,代码行数:18,代码来源:main.py 示例2: main ▲点赞 6▼ ...
neuralnetworks(CNNs)[LeCunetal.,1998]havebeensuccessfullyusedinvariousmachinelearningproblems,suchasimageclassification[Heetal.,2016]andspeechrecognition[Hintonetal.,2012],wherethereisanunderlyingEuclideanstructure.However,inmanyresearchareas,dataarenaturallylocatedinanon-Euclideanspace,withgraphornetworkbeingone...
To address this problem, we propose a novel framework called the Granularity Adaptive-Graph Wavelet Neural Network (GA-GWNN) to detect anomalies of online learners. The basic idea of GA-GWNN is to fuse graph convolutional neural networks and granular computing techniques to mine different types of...
(GWNN)Graph Wavelet Neural Network (ICLR2019) 用小波变换代替傅立叶变换实现图卷积。小波变换相对于傅立叶变换具有局部性,稀疏性和可解释性的性质,这些使得应用小波变换的图卷积神经网络更加高效,也满足了localize性质。 Wavelets on Graphs via Spectral Graph Theory ...
GWNNBingbing Xu et al.Graph Wavelet Neural Network (ICLR'19)✔️ ClusterGCNWei-Lin Chiang et al.Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks (KDD'19)✔️ DAGNNMeng Liu et al.Towards Deeper Graph Neural Networks (KDD'20)✔️✔️ ...