Tag: Causal Graph Neural Networks
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SDG-MoE: Advanced Signed Debate Graph Mixture-of-Experts
Discover SDG-MoE, a novel mixture-of-experts model using signed graphs for expert interaction, boosting AI performance and efficiency.
Graph Neural Networks for Real-Time Structural Displacement
Discover how Graph Neural Networks improve real-time structural displacement prediction, enhancing safety and efficiency in seismic monitoring.
Optimizing Graph Neural Networks for Electronic Design Automation
Explore how task-aligned Graph Neural Networks enhance Electronic Design Automation by matching circuit algebra with specific EDA challenges.
Defending GNN Backdoors with PRAETORIAN Trigger Analysis
Discover how PRAETORIAN defends GNNs by analyzing internal correlations and external influences to block backdoor attacks effectively.
Crystal Fractional GNN for Accurate HEA Energy Prediction
Discover how the crystal fractional graph neural network improves energy prediction accuracy in high-entropy alloys using AI-driven models.