Non-Stochastic Uncertainty Quantification with Applications

  • Date:
  • Time: 14:00 - 15:30
  • Address:
    Sokolovská 83, Praha
  • Room: K3
  • Speaker: Jan Chleboun

In applying mathematical and computational models, uncertainty in model inputs and, consequently, in model outputs should be assessed. Although stochastic methods are probably most popular in uncertainty quantification (UQ), non-stochastic approaches can be advantageous in some situations. The lecture will focus on two of them, namely on fuzzy set theory and Dempster-Shafer theory. It will be shown that even elementary tools offered by these theories and supplemented by the finite element method and optimization methods enables us to design algorithms for UQ in problems driven by, for instance, differential equations. Little prior knowledge of mathematics is assumed; the lecture will be accessible to undergraduate students.