Projects
Parametrized Model Order Reduction (PMOR): Sparse Data and Sparse Models Ghent University
The main objective of this project is the development of robust and stable rational modelling algorithms to build parametrized reduced order models for complex physical systems. The order and complexity of the scalable rational models are specifically tailored towards the application at hand. The approximation and/or interpolation models are based on sparse scatterded data,spread over the design space of interest, and the models are aimed at ...
Clustering Time Series KU Leuven
The notion of similarity is becoming more and more important in data analysis.
Comparing two objects quantitatively is a fundamental building block of most
machine learning algorithms, be it supervised or unsupervised. While for simple
mathematical objects, the notion of similarity might be intuitively clear (when
comparing how different two integers are, for example, we can just look at
the absolute difference ...