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Found 2 papers, 2 papers with code
Batch Bayesian optimisation via density-ratio estimation with guarantees
Bayesian optimisation (BO) algorithms have shown remarkable success in applications involving expensive black-box functions.
Variational Inference for Graph Convolutional Networks in the Absence of Graph Data and Adversarial Settings
We propose a framework that lifts the capabilities of graph convolutional networks (GCNs) to scenarios where no input graph is given and increases their robustness to adversarial attacks.
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