19234701
Lecture
SoSe 21: Gaussian measures in infinite dimensions and invariant measures for PDEs
Immanuel Zachhuber
Additional information / Pre-requisites
Prerequisites: Some knowledge of Probability and Functional Analysis
Comments
Content: The first aim of the course is to introduce Gaussian measures in Hilbert spaces and then on more general Banach spaces. Later we will use the insights we gained to construct ... read more
Suggested reading
Literature will be given at the beginning of the course or can be found on the Homepage.
14 Class schedule
Regular appointments
Tue, 2021-04-13 14:00 - 16:00
Tue, 2021-04-20 14:00 - 16:00
Tue, 2021-04-27 14:00 - 16:00
Tue, 2021-05-04 14:00 - 16:00
Tue, 2021-05-11 14:00 - 16:00
Tue, 2021-05-18 14:00 - 16:00
Tue, 2021-05-25 14:00 - 16:00
Tue, 2021-06-01 14:00 - 16:00
Tue, 2021-06-08 14:00 - 16:00
Tue, 2021-06-15 14:00 - 16:00
Tue, 2021-06-22 14:00 - 16:00
Tue, 2021-06-29 14:00 - 16:00
Tue, 2021-07-06 14:00 - 16:00
Tue, 2021-07-13 14:00 - 16:00
Gaussian measures in infinite dimensions and invariant measures for PDEs
Gaussian measures in infinite dimensions and invariant measures for PDEs
Gaussian measures in infinite dimensions and invariant measures for PDEs
Gaussian measures in infinite dimensions and invariant measures for PDEs
Gaussian measures in infinite dimensions and invariant measures for PDEs
Gaussian measures in infinite dimensions and invariant measures for PDEs
Gaussian measures in infinite dimensions and invariant measures for PDEs
Gaussian measures in infinite dimensions and invariant measures for PDEs
Gaussian measures in infinite dimensions and invariant measures for PDEs
Gaussian measures in infinite dimensions and invariant measures for PDEs
Gaussian measures in infinite dimensions and invariant measures for PDEs
Gaussian measures in infinite dimensions and invariant measures for PDEs
Gaussian measures in infinite dimensions and invariant measures for PDEs
Gaussian measures in infinite dimensions and invariant measures for PDEs