After successful completion of the course, students are able to identify problems with high-dimensional structure. They are equipped to estimate approximation errors as well as the cost of algorithms suitable for those problems.
Neural Networks for PDEs, Monte Carlo related methods, numerics of stochastic PDEs and PDEs with random coefficients,
Students prepare homework problems and present them in class
2/3*(number of prepared homework problems/ total number of homework problems) + 1/3*(presentation of the problems)