A hyperprior on the effective output variance of deep ReLU Bayesian neural networks yields simultaneously admissible and minimax decision rules in the normal location model under quadratic loss.
A bayesian neural network approach for modelling censored data with an application to prognosis after surgery for breast cancer
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Minimaxity and Admissibility of Bayesian Neural Networks
A hyperprior on the effective output variance of deep ReLU Bayesian neural networks yields simultaneously admissible and minimax decision rules in the normal location model under quadratic loss.