This course is concerned with randomized algorithms that have been developed during the last decade to solve large-scale linear algebra problems from, for example, scientific computing and statistical learning. Emphasis will be placed on both, the develop ...
The program of the School aims al providing the students with the main concepts and methodologies for developing a numerical model of superconducting devices. The students will learn numerical modelling techniques for different physical aspects of supercon ...
The objective of this course is to provide the necessary background for designing efficient parallel algorithms in scientific computing as well as in the analysis of large volumes of data. The operations considered are the most costly steps at the heart of ...
The course will cover some fundamentals of magnetohydrodynamics (MHD) theory with hands-on sessions to learn the basics of MHD simulations using the open-source Pencil Code (http://pencil-code.nordita.org/). ...
The literature on nonlinear signal processing has exploded, and it becomes more and more difficult to identify the most useful approaches for specific contexts. This course presents promising developments for the practical application of nonlinear signal m ...