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  "Description": "Cross-validated eigenvalues are estimated by splitting a\ngraph into two parts, the training and the test graph. The\ntraining graph is used to estimate eigenvectors, and the test\ngraph is used to evaluate the correlation between the training\neigenvectors and the eigenvectors of the test graph. The\ncorrelations follow a simple central limit theorem that can be\nused to estimate graph dimension via hypothesis testing, see\nChen et al. (2021) <doi:10.48550/arXiv:2108.03336> for details.",
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