Global Sensitivity Analysis in Stochastic Systems

This lecture by the instructor on March 29th, 2019, focuses on Variance-Based Sensitivity Analysis for Stochastic Ordinary Differential Equations (SODEs). The presentation covers the impact of parameters uncertainty in stochastic models, the decomposition of variance, and the sensitivity indices. Examples include sub-grid parametrization and different noise models. The lecture explores the application of Sobol Analysis for variance decomposition and the assessment of different reaction channels in stochastic simulators. Future work includes complex functional analysis and computational complexity reduction methods.