Tag: Causal Graph Neural Networks
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Robust Graph Self-Supervised Learning for Noisy Biomedical Text
Explore robust graph self-supervised learning methods for noisy biomedical text-driven graphs, improving accuracy by up to 7% over language models.
COPYCOP: Verify Ownership of Graph Neural Networks
COPYCOP offers reliable ownership verification for Graph Neural Networks, detecting copycat models and protecting intellectual property.
Magic-Informed Quantum Architecture Search for Quantum Advantage
Discover how Magic-Informed Quantum Architecture Search enhances quantum circuits using machine learning for improved quantum computing performance.
Hierarchy-Aware GNN Embeddings for Yeast Phenotype Prediction
Discover how hierarchy-aware graph neural network embeddings improve yeast phenotype prediction by leveraging knowledge graphs and semantic loss.
Graph Rewiring in GNNs to Fix Over-Squashing & Smoothing
Explore graph rewiring techniques to overcome over-squashing and over-smoothing in GNNs, enhancing performance and information flow in deep networks.