Encryption systems rely on “random” numbers, but conventional computers can’t generate them perfectly. New research shows that quantum physics can. By Alexander Nazaryan Researchers in Switzerland ...

experimenting by changing multiple factors (variables) simultaneously to efficiently identify 'which variables affect the results' and 'which combination is most effective'. However, the essence is ...

The Python Toolkit for Uncertainty Quantification (PyTUQ) is a Python-only collection of libraries and tools designed for quantifying uncertainty in computational models. PyTUQ offers a range of UQ ...

Modern multivariate analysis relies heavily on probabilistic modelling to capture the joint behaviour of multiple interdependent variables. At its core lies the formulation of a joint probability ...

In the rapidly developing field of data science, using visual representations to understand complex datasets is a necessity. One potent tool in this analytical arsenal is the radar chart, an ...

The joint probability of two or more variables being “extreme” is relevant in Flood and Coastal Risk Management (FCRM) in various contexts, including: Assessing the likelihood of extreme peak flow ...

The lectures on this page should be watched before the live sessions on Monday, June 13, 2022 (Tuesday, June 14 in some time zones). Total viewing time for this lecture series is 2 hours 16 minutes.

Note: Bold values indicate the statistical metrics of the best input. It can be concluded that the RF method is generally superior to the MARS method for the single-input temperature-, sunshine ...

Abstract: Moments of continuous random variables admitting a probability density function are studied. We show that, under certain assumptions, the moments of a random variable can be characterized in ...