Charalambos Makridakis: Approximations of Nonlinear Problems: Adaptive Algorithms and Analysis
- Slides and papers are available here
Grigorios Pavliotis: Sampling from probability measures using stochastic differential equations
- Lecture 1: Stochastic differential equations and the backward and forward Kolmogorov equations
- Lecture 2: Ergodic properties of SDEs and SDE-based sampling schemes for sampling from high dimensional distributions.
- Lecture 3: Numerical methods for SDEs, long time behaviour of numerical schemes.
- Lecture 4: Optimal SDE-based samplers.
Daniel Peterseim: Numerical homogenization beyond periodicity and scale separation
- Lecture notes: PDF
- Tutorials offered by Roland Maier
Evangelia Kalligiannaki: Indirect inference for probabilistic wind power forecast models with Itô stochastic differential equations
- Abstract: PDF
Konstantinos Spiliopoulos: Stochastic gradient descent in continuous time and deep learning for PDEs
- Abstract: PDF