Walk-Steered Convolution for Graph Classification

Computer Science

• Convolutional Neural Network 100%
• Receptive Field 66%
• Random Walk 66%
• Experimental Result 33%
• Principal Components 33%
• World Application 33%
• Higher Semantic Level 33%
• Subgraphs 33%
• Gaussian Mixture Model 33%
• Convolutional Network 33%
• Gaussian Model 33%
• Convolution Kernel 33%
• Public Data Set 33%

Engineering

• Convolutional Neural Network 100%
• Receptive Field 66%
• Gaussians 66%
• Nodes 33%
• Experimental Result 33%
• Internals 33%
• Multiscale 33%
• Gaussian Mixture Model 33%
• Principal Components 33%
• Real World Application 33%
• Level Semantics 33%
• Gaussian Model 33%

Mathematics

• Dynamic Clustering 33%
• Euclidean Topology 33%