Research
SNSF Starting grant: Multiresolution methods for unstructured data
Rapidly increasing unstructured data is omnipresent in our everyday lives.
Typical examples are data from social networks, text and audio data,
photos and videos, but also scientific measurements and simulation data.
Efficient processing and analysis of these data have become vital for our
society.
In "Multiresolution methods for unstructured data", we develop novel and
fully discrete data-centric multiresolution approaches tailored to
unstructured data, focusing on efficient algorithms for computational
uncertainty quantification and adaptive strategies for active learning and
non-smooth data.
Results obtained in this project will be made available within the
software package FMCA (Link: https://github.com/muchip/fmca).
