Abstract: Network resilience, defined as the ability of a network to maintain its functionality under failure or adversarial conditions, is a crucial consideration in the design and deployment of ...
Abstract: Graph contrastive learning (GCL) leverages semantic consistency as contrastive signals and has shown strong performance in semi-supervised node classification. However, real-world graphs ...
Researchers have demonstrated a new training technique that significantly improves the accuracy of graph neural networks (GNNs)—AI systems used in applications from drug discovery to weather ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results