{"id":5,"date":"2019-10-22T13:04:03","date_gmt":"2019-10-22T13:04:03","guid":{"rendered":"https:\/\/unequivocal.computationalscience.nl\/?page_id=5"},"modified":"2022-02-21T10:12:08","modified_gmt":"2022-02-21T10:12:08","slug":"main-page","status":"publish","type":"page","link":"https:\/\/unequivocal.computationalscience.nl\/","title":{"rendered":"Uncertainty Quantification for Computational Models"},"content":{"rendered":"\n

The UNEQUIvOCAL thematic track is organized as a part of the International Conference on Computational Science ICCS 2022<\/a> that will be held in London<\/strong>, United Kingdom from 21 to 23 June 2022<\/strong>.<\/p>\n\n\n\n

This will be the third edition of the UNEQUIvOCAL thematic track. In 2021, the thematic track was part of the online ICCS 2021. The 2020 edition was a part of the online conference on Multiscale Modelling, Uncertainty Quantification and the Reliability of Computer Simulations<\/a>. The recordings of day one<\/a> and day two<\/a> of the conference are available.<\/p>\n\n\n\n

About<\/h1><\/span>\n\n\n\n

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 of 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.\u00a0Also, 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.\u00a0This thematic track aims to attract research that focuses on new methods, which outperform existing techniques, as well as uncertainty quantification applications to complex problems.<\/p>\n\n\n\n

Topics of interest<\/h1><\/span>\n\n\n\n