graph neural networks

Self-organizing memristive networks as physical learning systems

Graph neural network-based service migration decision in vehicular networks

The rapid development of the Internet of Vehicles (IoV) has led to an exponential increase in the number of latency sensitive and computationally intensive tasks. Due to the limitations of onboard computing resources in vehicles, offloading these tasks generated during vehicle operation to a remote cloud for processi...

Beyond direct AI exposure: Measuring network-mediated labor risk through multilayer occupational networks

Data‐Driven Spectral Prediction for Accelerating Large‐Scale Electronic Structure Calculations

ABSTRACT Simulating large molecular systems comprising thousands of atoms requires highly scalable methodologies. While modern Density Functional Theory (DFT) codes exhibit linear scaling, solving the associated large, sparse generalized eigenproblems remains a critical computational bottleneck on exascale architecture...

Optimization of Resource Allocation in 5G Networks Using Game Theory-Based Algorithms

Experimental results on a realistic 5G QoS dataset demonstrate significant improvements over baseline methods, including higher throughput, lower latency, improved fairness, reduced packet loss, and enhanced energy efficiency, confirming the framework's scalability and QoS awareness.

An Edge-Deployable Lightweight Dynamic Spatio-Temporal Graph Neural Network for Joint Distribution-Network Line-Loss Prediction and Operating-State Recognition

A lightweight dynamic spatio-temporal graph neural network, EdgeLite-DSTGNN, is proposed to address the intensified spatio-temporal coupling of line-loss rates, complex state correlations, and limited edge-terminal resources in distribution networks with high renewable-energy penetration. The method treats branches as...

Revealing environmental associations underlying seasonal distribution of Pacific yellowfin tuna species with geospatial neural networks

Yellowfin tuna ( Thunnus albacares ) is a highly migratory and economically important species in the Pacific Ocean, and its spatial distribution is closely associated with marine environmental conditions. To investigate the environmental associations underlying the spatial patterns of yellowfin tuna nominal catch p...

Mechanism-aware and safety-validated AI for drug repurposing: a critical review and translational pharmacology framework

This critical review summarizes existing AI approaches to drug repurposing, identifies their mechanistic, safety, and translational barriers, and incorporates the emerging evidence gaps into a mechanism-driven and safety-proven translational pharmacology model.

A novel FedLLM intrusion detection framework for privacy-preserving security in IoT enabled smart city network

Editorial: Exploring neuropsychiatric disorders through multimodal MRI: network analysis, biomarker discovery, and clinical insights

The research included in this Research Topic span a broad range of conditions, including neurodevelopmental disorders, psychiatric disorders, neurodegenerative diseases, infection-related brain injury, pain-related disorders, disorders of consciousness, and spinal disorders affecting the nervous system. Despite the div...

Harmonizing Predictive Accuracy and Cooperative Outcomes in Game-Theoretic Systems

A novel framework in which predictions lead to Nash equilibria that can either prioritize precise outcomes or foster broader social benefits two objectives often in tension is proposed, highlighting the synergistic benefits of combining graph-based models with centralized systems to encourage cooperation.

Big Data-Driven Production Scheduling Risk Identification Using a Lightweight Adaptive Graph Attention Network.

The advancement of Industry 4.0 and smart manufacturing has led to the generation of high-volume, multisource data that evolve in real-time within production scheduling systems. This poses significant challenges to traditional risk identification methods. Models that ignore topological relationships lack robustness whe...