Alpha-divergence minimization with mixed variational posterior for Bayesian neural networks and its robustness against adversarial examples

•We develop alpha-divergence minimization with mixed variational posterior.•The proposed method is time-efficient and extendable to various neural networks.•We provide the uncertainty comparison of Bayesian neural networks adopting different posterior approximations.•Experimental results show that our method achieves higher performance.