IEEE

Graph Neural Network Algorithm Based on Graph Convolution and Attention Mechanism

Abstract: With the wide application of graph neural network (GNN) in many fields, how to extract and aggregate node features effectively has become a hot research issue. In this paper, we propose a ...
sei.cmu

Graph Convolutional Neural Networks

Our approach employed topology-adaptive graph convolutional networks, introduced in 2017 by researchers at Carnegie Mellon University. This new class of GCNNs is grounded in graph signal processing ...
IEEE

Data-Driven Dynamic Graph Convolution Transformer Network Model for EEG Emotion Recognition Under IoMT Environment

Abstract: With the rapid progress in data-driven approaches, artificial intelligence, and big data analytics technologies, utilizing electroencephalogram (EEG) signals for emotion analysis in the ...
GitHub

chen26sanken/Utilizing-Molecular-Descriptors-in-Graph-Convolutional-Neural-Networks

¹ SANKEN, The University of Osaka, Mihogaoka 8-1, Ibaraki, Osaka, 567-0047, JAPAN ² Graduate School of Information Science and Technology, The University of Osaka, Yamadaoka 1-5, Suita, 565-0871, ...
Houston Chronicle

How to Graph a Cube in MATLAB

Not every sample of data can be meaningfully plotted on a two-dimensional graph. MATLAB, a technical analysis software suite from MathWorks, allows you to plot publication-quality, three-dimensional ...