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Graph convolutional neural networks (GCNN) have been successfully applied to many different graph based learning tasks including node and graph classification, matrix completion, and learning of node embeddings.
Bayesian learning via stochastic dynamics
Radford M. Neal · 1993
Earlier work this paper cites.
Maximum entropy and Bayesian methods , chapter Hyperparameters: Optimize, or Integrate Out?, pp. 43–59
David J. C. MacKay · 1996
Earlier work this paper cites.
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