Tensor methods in stochastic PDEs and in inverse problems

After discretization of stochastic PDEs (PDEs with uncertain coefficients) one obtains a high dimensional problem. Usual methods have very high exponential cost and do not work. Therefore we apply low-rank tensor methods to solve the problem and to perform post processing (computing different statistics) in an efficient way with a low computational cost. Some open problems will be highlighted at the end of the talk.