🌐 Entity

Graph neural network

Class of artificial neural networks

📊 Rating

7 news mentions · 👍 0 likes · 👎 0 dislikes

📌 Topics

Artificial Intelligence (7)
Cybersecurity (2)
Data Science (2)
Robotics (2)
Logistics (1)
Manufacturing (1)
Network Infrastructure (1)
Mathematics (1)
Pathfinding (1)
Computer Science (1)
Cloud Computing (1)
Edge Computing (1)

🏷️ Keywords

Graph Neural Networks (7) · arXiv (5) · GNN (3) · Deep Reinforcement Learning (1) · Parallel Machine Scheduling (1) · Proximal Policy Optimization (1) · Industrial Automation (1) · UPMSP (1) · Zero-day threats (1) · Firewall automation (1) · Pro-ZD (1) · Network security (1) · Machine learning (1) · ATEX-CF (1) · Counterfactual Explanations (1) · Adversarial Attacks (1) · Machine Learning Interpretability (1) · Graph Shift Operator (1) · Spectral Analysis (1) · Machine Learning (1)

📖 Key Information

Graph neural networks (GNN) are specialized artificial neural networks that are designed for tasks whose inputs are graphs. One prominent example is molecular drug design. Each input sample is a graph representation of a molecule, where atoms form the nodes and chemical bonds between atoms form the edges.

📰 Related News (7)

🇺🇸 Graph-Enhanced Deep Reinforcement Learning for Multi-Objective Unrelated Parallel Machine Scheduling (2026-02-10)
arXiv:2602.08052v1 Announce Type: new Abstract: The Unrelated Parallel Machine Scheduling Problem (UPMSP) with release dates, setups, and eligibility...
🇺🇸 Pro-ZD: A Transferable Graph Neural Network Approach for Proactive Zero-Day Threats Mitigation (2026-02-10)
arXiv:2602.07073v1 Announce Type: cross Abstract: In today's enterprise network landscape, the combination of perimeter and distributed firewall rule...
🇺🇸 ATEX-CF: Attack-Informed Counterfactual Explanations for Graph Neural Networks (2026-02-09)
arXiv:2602.06240v1 Announce Type: cross Abstract: Counterfactual explanations offer an intuitive way to interpret graph neural networks (GNNs) by ide...
🇺🇸 Which Graph Shift Operator? A Spectral Answer to an Empirical Question (2026-02-09)
arXiv:2602.06557v1 Announce Type: cross Abstract: Graph Neural Networks (GNNs) have established themselves as the leading models for learning on grap...
🇺🇸 Pairwise is Not Enough: Hypergraph Neural Networks for Multi-Agent Pathfinding (2026-02-09)
arXiv:2602.06733v1 Announce Type: cross Abstract: Multi-Agent Path Finding (MAPF) is a representative multi-agent coordination problem, where multipl...
🇺🇸 Scaling Multi-Agent Epistemic Planning through GNN-Derived Heuristics (2026-02-09)
arXiv:2508.12840v4 Announce Type: replace Abstract: Multi-agent Epistemic Planning (MEP) is an autonomous planning framework for reasoning about both...
🇺🇸 Adaptive AI-based Decentralized Resource Management in the Cloud-Edge Continuum (2026-02-09)
arXiv:2501.15802v2 Announce Type: replace-cross Abstract: In the Cloud-Edge Continuum, dynamic infrastructure change and variable workloads complicat...

🔗 Entity Intersection Graph

People and organizations frequently mentioned alongside Graph neural network:

🌐 GNN (3 shared articles)
🌐 Machine learning (2 shared articles)
🌐 Automation (1 shared articles)
🌐 Proximal policy optimization (1 shared articles)
🏢 Resource management (1 shared articles)
🌐 Spectral analysis (1 shared articles)
🌐 Network security (1 shared articles)
🌐 Kripke structure (model checking) (1 shared articles)
🌐 Collision avoidance system (1 shared articles)
🌐 Deep learning (1 shared articles)

Точка Синхронізації