Learning Stochastic Graph Neural Networks With Constrained Variance
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DOI: 10.1109/tsp.2023.3244101
Abstract: Stochastic graph neural networks (SGNNs) are information processing architectures that learn representations from data over random graphs. SGNNs are trained with respect to the expected performance, which comes with no guarantee about deviations of particular… read more here.
Keywords: neural networks; variance constrained; stochastic graph; graph neural ... See more keywords