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Finite-Time Node Separation in Recurrent Graph Neural Networks with Persistent Gaussian Perturbations
Persistent Gaussian perturbations have been shown to prevent asymptotic oversmoothing in recurrent Graph Neural Networks (GNNs) by ensuring a positive stationary Dirichlet energy. However, this global energy bound does not guarantee that individual node representations remain distinct at finite dept
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