arXiv (OAI Expanded)
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Online Bayesian Node Classification on Inductive Graphs under Distribution Shift
On evolving graphs, node classifiers must satisfy two key requirements: inductive generalization to newly arriving nodes under distribution shift and calibrated uncertainty for safety-sensitive applications. Standard graph neural networks (GNNs) are typically trained once and address neither require
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