The UNEQUIvOCAL thematic track is organized during the International Conference on Computational Science ICCS 2020 in Amsterdam, The Netherlands, June 3 – June 5, 2020.
Given that uncertainty is unavoidable in almost all scientific fields, due to e.g. unknown parameters or simplifying modelling assumptions, uncertainty quantification is an indispensable part in state-of-the-art computational models. In order to build confidence in their results, it is therefore crucial that these models carry their own measure of uncertainty, especially when they are extrapolated beyond the domain in which they were originally calibrated. Also, the oncoming Exascale Computing resources will open up the possibility of solving problems with increased complexity and computational burden, exacerbating the importance (and demands) of reliable uncertainty quantification methods. This thematic track aims to attract research that focuses on new methods, which outperform existing techniques, as well as uncertainty quantification applications to complex problems.
Topics of interest
- Forward and inverse uncertainty quantification;
- Sensitivity analysis;
- Dimension reduction;
- Surrogate modelling (including machine-learning techniques and reduced-order modelling);
- Case studies showing efficient uncertainty quantification methods;
- Software for uncertainty quantification.