IEEE

Decoupled Dynamic Spatial–Temporal Graph Neural Network for Sea Surface Temperature Prediction

Abstract: Accurate sea surface temperature (SST) prediction is essential for advancing the understanding of marine ecosystems and global climate dynamics. SST variations arise from a dynamic interplay ...
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) ...
EurekAlert!

PolyU develops novel AI graph neural network models to unravel interdisciplinary complexities in image recognition and neuroscience

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...
GitHub

Neural Network from Scratch

Eric Gutiérrez, 6th February 2026. A Python implementation of a 1-hidden layer neural network built entirely from first principles. This project avoids deep learning libraries (like TensorFlow or ...