A new approach to Bayesian inference, named the prior-free inference, is introduced for developing objective Bayesian analysis based on information-theoretic approach. This new approach is essentially a Bayesian method but it does not depend on a prior distribution for unknown parameters. Thus, this approach not only has the advantages of the Bayesian approach but also can avoid the difficulty,...

We present a method to generate renewable scenarios using Bayesian probabilities by implementing the Bayesian generative adversarial network (Bayesian GAN), which is a variant of generative adversarial networks based on two interconnected deep neural networks. By using a Bayesian formulation, generators can be constructed and trained to produce scenarios that capture different salient modes in ...