This is a graph convolution implementation in Keras. Unlike CNN that does convolution among input sources regardless they are related or not, graph convolution only does convolution over related input ...

The Graph Diffusion Convolution (GDC) technique presented in this paper demonstrates how incorporating diffusion processes can enhance graph learning. By leveraging graph diffusion, GDC can ...

Graph convolution machine for context-aware recommender system. Higher Education Press . Journal Frontiers of Computer Science Funder National Key Research and Development Program of China, ...

In this paper, we present a novel convolution theorem which encompasses the well known convolution theorem in (graph) signal processing as well as the one related to time-varying filters. Specifically ...

After the graphic signals are constructed, EEG feature data is performed through two graph convolution layers, two Relu layers (Glorot et al., 2011), two graph pooling layers (Ouhmich et al., 2019), ...

In this article, a novel R-convolution kernel, named the fast quantum walk kernel (FQWK), is proposed for unattributed graphs. In FQWK, the similarity of the neighborhood-pair substructure between two ...