CECF is a new causal framework for edge classification that balances high-dimensional edge features against node influences via GNN embeddings and cross-attention to achieve better performance than standard methods.
Canonical correlation analysis: An overview with application to learning methods.Neural computation, 16(12):2639–2664
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Advancing Edge Classification through High-Dimensional Causal Modeling of Node-Edge Interplay
CECF is a new causal framework for edge classification that balances high-dimensional edge features against node influences via GNN embeddings and cross-attention to achieve better performance than standard methods.