In this article, a novel approach for training deep neural networks using Bayesian techniques is presented. The methodology allows an easy evaluation of model uncertainty and, additionally, robust to overfitting. These are commonly the two main problems classical, i.e., non-Bayesian architectures have struggle with. proposed applies variational inference in order approximate intractable posteri...

In a simple dynamic macroeconomic model, it is shown that uncertainty about structural parameters does not necessarily lead to more cautious monetary policy, refining the accepted wisdom concerning the effects of parameter uncertainty on optimal policy. In particular, when there is uncertainty about the persistence of inflation, it may be optimal for the central bank to respond more aggressivel...

This paper considers the application of method of percentile matching available in statistical theory of estimation for estimating the parameters involved in uncertainty distributions. An empirical study has been carried out to compare the performance of the proposed method with the method of moments and the method of least squares considered by Wang and Peng (J. Uncertainty Analys. Appl. 2, (2...

Facility location decisions play a prominent role in strategic planning of many firms, companies and governmental organizations. Since in many real-world facility location problems, the data are subject to uncertainty, in this paper, we consider the P-center problem under uncertainty of demands. Using Bertsimas and Sim approach, we develop a robust model of the problem as an integer programming...

Natural hazards such as earthquakes have threatened the life of human beings during the history.As a consequence, the vibration mitigation of structures has caught great importance. Activecontrol of structures is one of the rapidly emerging areas in the concept of structural control. Thispaper presents a control method to deal with this subject when the dynamics of the structure ishysteretic an...

The uncertainty principle plays an important role in mathematics, physics, signal processing, and so on. Firstly, based on definition of the linear canonical transform (LCT) and the traditional Pitt’s inequality, one novel Pitt’s inequality in the LCT domains is obtained, which is connected with the LCT parameters a and b. Then one novel logarithmic uncertainty principle is derived from this no...