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Optimal transport provides a surprisingly tight and efficiently computable bound on transductive generalization in graph node classification, revealing how GNN depth impacts representation geometry.
Skip the retraining: compose pre-trained GFlowNets at inference time to tackle multi-objective generation, even with complex non-linear reward functions.
