This course aims to develop a computational view of stochastic differential equations (SDEs) for students who have an applied or engineering background, e.g., machine learning, signal processing, ...
Introduction: Accurately predicting the remaining mechanical equipment is of great significance for ensuring the safe operation of the equipment and improving economic efficiency. Methods: To ...
ABSTRACT: In this paper, a bivariate stochastic process with Poisson postulates has been considered to model the incomings, outgoings and mutual transfers of investments between and within the ...
The 2025 edition of the traditional Boltzmann Lecture will be held on Thursday, February 20th, at 14:00 in Room 128-129. Professor Satya Majumdar from CNRS and Universite Paris-Sud, Orsay will give a ...
In this workshop, we will talk about a variety of stochastic process models, give their definitions. We will discuss the underlying assumptions and theory for the models. Then we will then explore ...
School of Mathematics and Statistics, Southwest University, Chongqing, China. Stochastic differential equations (SDEs) have been intensively used to model the natural phenomena in the last decades and ...
Abstract: This paper proposes a stochastic process based remaining useful life (RUL) prediction method for hybrid systems in the presence of intermittent fault. The failure of an intermittently faulty ...
In machine learning, deterministic and stochastic methods are utilised in different sectors based on their usefulness. A deterministic process believes that known average rates with no random ...
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