IEEE

Hybrid Network Using Dynamic Graph Convolution and Temporal Self-Attention for EEG-Based ...

Abstract: The electroencephalogram (EEG) signal has become a highly effective decoding target for emotion recognition and has garnered significant attention from researchers. Its spatial topological ...
GitHub

GraphGPT: Graph Instruction Tuning for Large Language Models

Data Intelligence Lab@University of Hong Kong, Baidu Inc. This repository hosts the code, data and model weight of GraphGPT (SIGIR'24 full paper track). Due to compatibility issues, if you are using ...
GitHub

Graph Neural Network-Based Anomaly Detection (GNNAD)

gnnad is a package for anomaly detection on multivariate time series data. This model builds on the recently-proposed Graph Deviation Network (GDN) 1, a graph neural network model that uses embeddings ...
IEEE

Federated Graph Neural Networks: Overview, Techniques, and Challenges

Abstract: Graph neural networks (GNNs) have attracted extensive research attention in recent years due to their capability to progress with graph data and have been widely used in practical ...