Specifically, we model the inter-channel relations in EEG signals via an adjacency matrix in a graph neural network where the connection and sparseness of the adjacency matrix are inspired by ...

Implementation of various neural graph classification model (not node classification) Training and test of various Graph Neural Networks (GNNs) models using graph classification datasets; Input graph: ...

BingoCGN, a scalable and efficient graph neural network accelerator that enables inference of real-time, large-scale graphs ...

The brains of humans and other primates are known to execute various sophisticated functions, one of which is the ...

The graph neural network (GNN) exhibits noteworthy performance in hyperspectral image classification (HSIC) due to its efficient message-passing structure, which employs the multilayer perceptron (MLP ...