AINeutralarXiv – CS AI · 5h ago6/10
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Learning to Execute Graph Algorithms Exactly with Graph Neural Networks
Researchers demonstrate that graph neural networks can learn to execute classical graph algorithms exactly through a two-step training process combining MLPs with NTK theory. The work establishes rigorous theoretical learnability results for distributed computing models and practical algorithms like breadth-first search and Bellman-Ford, advancing understanding of what GNNs can provably learn.