IEEE

Dynamical Causal Graph Neural Network for EEG Emotion Recognition

Abstract: Recently, topological graphs based on structural or functional connectivity of brain network have been utilized to construct graph neural networks (GNN) for Electroencephalogram (EEG) ...
Live Science

Scientists create world's first microwave-powered computer chip — it's much faster and consumes less power than conventional CPUs

A new kind of processor that uses microwaves can be used in future AI systems or in wireless communications, a new study shows. When you purchase through links on our site, we may earn an affiliate ...
IEEE

RandomViG: Random Vision Graph Neural Network for Image Classification

Abstract: Vision Graph Neural Network (ViG) is the first graph neural network model capable of directly processing image data. The community primarily focuses on the model structures to improve ViG's ...
Frontiers

DGAT: a dynamic graph attention neural network framework for EEG emotion recognition

Introduction: Emotion recognition based on electroencephalogram (EEG) signals has shown increasing application potential in fields such as brain-computer interfaces and affective computing. However, ...
EurekAlert!

Real-time, large-scale graph neural network inference through BingoCGN

BingoCGN employs cross-partition message quantization to summarize inter-partition message flow, which eliminates the need for irregular off-chip memory access and utilizes a fine-grained structured ...