Introduction to the basic techniques of image processing. Introduction to the development of image-processing software and to prototyping using Jupyter notebooks. Application to real-world examples in industrial vision and biomedical imaging. ...
Nonparametric models are used to identify a wide range of relationships within data. This course gives a graduate-level overview of nonparametric statistical estimation and inference theory. ...
This course assumes familiarity with beginning graduate level real analysis, complex analysis and functional analysis, and also basic
harmonic analysis, as well as fundamental concepts from differential geometry. ...
The course will provide the opportunity to tackle real world problems requiring advanced computational skills and visualisation techniques to complement statistical thinking. Students will practice proposing efficient solutions, and effectively communicati ...
We develop, analyze and implement numerical algorithms to solve optimization problems of the form min f(x) where x is a point on a smooth manifold. To this end, we first study differential and Riemannian geometry (with a focus dictated by computational con ...
In the decades from 1930 to 1950, many rank-based statistics were introduced. These methods were received with much interest, because they worked under weak conditions. Starting in the late 1950, a theory of robustness was added. The course gives an overvi ...
Students study & apply core concepts and algorithms for digital geometry processing. They create their own digital and physical geometry that follows the digital 3D content creation pipeline from data acquisition, geometry processing, to physical fabricati ...