Numerical methods for uncertainty quantification [MAT08, 2 ECTS]

Speaker:  Chiara Piazzola - Technical University of Munich
  Wednesday, April 3, 2024 (starting from, 2 weeks)

The aim of this course is to provide an introduction to uncertainty quantification for differential equations 
with random coefficients. We will focus on the forward problem of assessing the propagation of the 
uncertainty in the input coefficients to the solution of the equation and discuss some standard and 
state-of-the-art computational methods, such as the Monte Carlo method, sparse grids, and the polynomial chaos
expansion. Moreover, we will address multi-fidelity techniques, such as the multi-level Monte Carlo method and  
multi-index stochastic collocation, that leverage low and high-fidelity model solutions to achieve the best 
trade-off between accuracy and computational cost. To complement the discussion, we will present some real-world applications.  


Programme Director
Marco Caliari

External reference
Publication date
December 22, 2023

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