Learn to apply Bayes' theorem in financial forecasting for insightful, updated predictions. Enhance decision-making with ...

The design and construction of capital projects can be extremely complex. Uncertainty and risk add to this complexity and, as a result, many projects experience significant cost overruns and schedule ...

What Is A Probabilistic Model? A probabilistic model is a statistical tool that accounts for randomness or uncertainty when predicting future events. Instead of giving a definitive answer, it ...

Probabilistic methods are increasingly being used to complement deterministic methods in assessing the safety and ensuring the reliability of research reactors. Addressing features specific to ...

The Annals of Applied Probability, Vol. 25, No. 3 (June 2015), pp. 1189-1231 (43 pages) Mean field games are studied by means of the weak formulation of stochastic optimal control. This approach ...

Saksman's research deals with several mathematical problem areas that involve probabilistic questions in various setups. These include probabilistic methods in mathematical physics, analysis and ...

Learn to address the likelihood of structural failure. Perform risk analysis associated with environmental loads to structures under static and dynamic loadings. Master the basics of performance-based ...