graph neural networks

Dynamic routing and wavelength assignment in optical networks: from capacity limits to flow-based control

Graph Neural Networks for Diffusion and Aggregation in Wireless Federated Learning

User devices (UDs) with non-independent and identically distributed (non-IID) data will worsen accuracy performance of the global model in federated learning (FL). Therefore, the implementation of diffusion strategies in machine learning (ML) models can enhance the effectiveness of federated learning with non-IID data....

ST-KFNet-Based Framework for Online Metro Passenger OD Demand Forecasting under Uncertainty

A novel spatiotemporal Kalman filter network (ST-KFNet) framework for metro demand forecasting by integrating an autoregressive integrated moving average module, a Kalman filter (KF) module, and a convolutional neural network (CNN)-based variational autoencoder (VAE) module is proposed.

Enhancing agent-based wayfinding simulation for transportation hub evaluation with a visual memory graph Neural network (VM-GNN)

A graph neural network-based framework for hierarchical time series forecasting in retail

Multi-scale dynamic graph neural networks for response prediction and anomaly detection in ancient timber structures

Malope: Memory-Aware and Locality-Preserved Graph Neural Network Training

Training GNNs on large-scale graphs imposes significant memory constraints for storing substantial amounts of graph structures and node features. This often necessitates the use of memory extensions such as SSDs, leading to a memory hierarchy with disparities in capacity and access speed. Existing approaches focus on m...

A spectral heterogeneous graph neural network with multi-sensor fusion for machine fault diagnosis

VulGNN: A high-fidelity graph neural network framework for robust smart contract vulnerability detection

EdgeSAC: Graph Neural Soft Actor-Critic for Hierarchical IoV Resource Management

Intelligent Transportation Systems (ITS) rely on the Internet of Vehicles (IoV) to sustain high data rates and low latency under dynamic and heterogeneous conditions. Joint power and spectrum control across macro and micro tiers remains challenging due to mobility, interference coupling, and large continuous action spa...

Sustainable energy management in IoT-enabled hybrid microgrids via graph neural network-optimized automatic generation control

Automated generation and surrogate modeling of 3D urban wind simulation based on physics-informed graph neural networks: a two-stage framework