Information in the lecture Machine Learning for Stochastics (SS 2025)

Lecturer: Prof. Dr. Thorsten Schmidt

Assistant: Simone Pavarana, M.Sc.

Lecture: Wed, 12-14 Uhr, HS II, Albertstr. 23b

Tutorial: 2 hours per week, date to be determined

Language: English

Content

In this lecture we will study new and highly efficient tools from machine learning which are applied to stochastic problems. This includes neural SDEs as a generalisation of stochastic differential equations relying on neural networks, transformers as a versatile tool not only for languages but also for time series, transformers and GANs as generator of time series and a variety of applications in Finance and insurance such as (robust) deep hedging, signature methods and the application of reinforcement learning.

News

Lecture notes / Course materials

Exercise sheets

To succeed in the pass/fail examination, you should earn at least 50% of the maximally accessible exercise points and additionally present one solution of an exercise in the tutorial.

Final exam

Consultation hours

Lecturer:
Assistant:

For shorter questions, you can also send an email to simone.pavarana@stochastik.uni-freiburg.de