IEEE

AWKNet: A Lightweight Neural Network for Motor Imagery Electroencephalogram Classification Based on Adaptive Wavelet Transform Kolmogorov-Arnold

Abstract: Motor imagery electroencephalography (MI-EEG) is widely used in the neural rehabilitation field, including for hybrid device control, such as robotic arms. However, it is difficult to apply ...
Medical Xpress

Rethinking how our brains build the neural networks underlying motor memories

For every motor skill you've ever learned, whether it's walking or watchmaking, there is a small ensemble of neurons in your brain that makes that movement happen. Our brains trigger these ...
GitHub

STM-Graph: A Python Framework for Spatio-Temporal Mapping and Graph Neural Network Predictions

STM-Graph is a Python framework for analyzing spatial-temporal urban data and doing predictions using Graph Neural Networks. It provides a complete end-to-end pipeline from raw event data to trained ...
IEEE

Hierarchy-Aware Adaptive Graph Neural Network

Abstract: Graph Neural Networks (GNNs) have gained attention for their ability in capturing node interactions to generate node representations. However, their performances are frequently restricted in ...