MB05 | Stochastik | Anton Bovier |
|
20151 611100905 Vorlesung SWS |
Termine: |
Mi 10-12 | Kleiner Hörsaal, Wegelerstr. 10
| |
Mo 10-12 | Kleiner Hörsaal, Wegelerstr. 10
| |
|
Link to Basis |
|
MB05 | Übungen zu Stochastik | Anton Bovier |
|
20151 611300905 Seminar/Übungen SWS |
Termine: |
Fr 12-14 | SemR 0.008, Endenicher Allee 60
| Gruppe 3
|
Di 12-14 | SemR 0.008, Endenicher Allee 60
| Gruppe 1
|
Di 12-14 | SemR 1.007, Endenicher Allee 60
| Gruppe 4, NEU!
|
Do 16-18 | SemR 0.008, Endenicher Allee 60
| Gruppe 2
|
|
Link to Basis |
|
S1G1 | Seminar | |
|
20151 611100109 Seminar SWS |
Termine: |
Di 10-12 | SemR 1.007, Endenicher Allee 60
| |
Do 10-12 | N 0.008 - Neubau, Endenicher Allee 60
| Vorbesprechung: Di, 24.02.15, 13:00, N0.008
|
Mi 12-14 | SemR 0.006, Endenicher Allee 60
| Vorbesprechung: 24.2.15, 13.30, Raum We6, 5.002
|
Fr 12-14 | - | |
Do 14-16 | SemR 0.003, Endenicher Allee 60
| Vorbesprechung: Do, 29.01.15, 16:00, Raum 4.050 EN60
|
Fr 14-16 | SemR 1.007, Endenicher Allee 60
| |
Mo 16-18 | N 0.003 - Neubau, Endenicher Allee 60
| |
|
Link to Basis |
|
S2F1 | Hauptseminar Stochastik | Karl-Theodor Sturm |
|
20151 611112011 Hauptseminar SWS |
Termine: |
Fr 14-16 | SemR 0.006, Endenicher Allee 60
| |
|
Link to Basis |
|
S2F1 | Hauptseminar Stochastik - Stochastische Modelle | Andreas Eberle |
|
20151 611111011 Hauptseminar SWS |
Termine: |
Fr 14-16 | SemR 0.007, Endenicher Allee 60
| |
|
Link to Basis |
|
S4F2 | Graduate Seminar on Stochastic Analysis - Interacting Particle Systems | Andreas Eberle |
|
20151 611501024 Hauptseminar SWS |
Termine: |
Di 14-16 | N 0.007 - Neubau, Endenicher Allee 60
| |
|
Link to Basis |
|
S5G1 | Master´s Thesis Seminar | |
|
20151 611500101 Seminar für Examenskandidaten SWS |
Termine: |
- | - | woech more lecturers according to prior agreement
|
Fr 12-14 | - | |
Do 16-17 | SemR 0.011, Endenicher Allee 60
| appointments with examiners according to prior agreement
|
|
Link to Basis |
|
V1G6 | Algorithmische Mathematik II | Martin Rumpf Anton Bovier |
|
20151 611100106 Vorlesung SWS |
Termine: |
Mo 10-12 | Großer Hörsaal, Wegelerstr. 10
| |
Mi 10-12 | Großer Hörsaal, Wegelerstr. 10
| |
|
Link to Basis |
|
V1G6 | Übungen zu Algorithmischer Mathematik II | Martin Rumpf Anton Bovier |
|
20151 611300106 Übung SWS |
Termine: |
Fr 08-10 | SemR 0.003, Endenicher Allee 60
| Gruppe 7
|
Fr 08-10 | SemR 0.007, Endenicher Allee 60
| Gruppe 8
|
Di 10-12 | SemR 0.007, Endenicher Allee 60
| Gruppe 1
|
Do 10-12 | SemR 0.003, Endenicher Allee 60
| Gruppe 4
|
Do 12-14 | SemR 0.003, Endenicher Allee 60
| Gruppe 5
|
Fr 12-14 | SemR 0.003, Endenicher Allee 60
| Gruppe 9
|
Fr 14-16 | SemR 0.003, Endenicher Allee 60
| Gruppe 10
|
Di 16-18 | SemR 0.007, Endenicher Allee 60
| Gruppe 3
|
Do 16-18 | SemR 0.003, Endenicher Allee 60
| Gruppe 6
|
|
Link to Basis |
|
V2F2 | Einführung in die Statistik | Martin Huesmann |
|
20151 611100703 Vorlesung SWS |
Termine: |
Mo 12.00-14.00 | Großer Hörsaal, Wegelerstr. 10
| |
Mi 12.00-14.00 | Großer Hörsaal, Wegelerstr. 10
| |
|
Link to Basis |
|
V2F2 | Übungen zu Einführung in die Statistik | Martin Huesmann |
|
20151 611300703 Übung SWS |
Termine: |
Do 14-16 | SemR 1.008, Endenicher Allee 60
| Gruppe 2
|
Mi 16-18 | SemR 0.008, Endenicher Allee 60
| Gruppe 1
|
Do 18-20 | SemR 1.008, Endenicher Allee 60
| Gruppe 3
|
|
Link to Basis |
|
V3F1/F4F1 | Stochastic Processes / Stochastische Prozesse | Karl-Theodor Sturm |
|
20151 611100702 Vorlesung SWS |
Termine: |
Di 08-10 | Kleiner Hörsaal, Wegelerstr. 10
| |
Fr 10-12 | Kleiner Hörsaal, Wegelerstr. 10
| |
|
Link to Basis |
|
V3F1/F4F1 | Exercises to Stochastic Processes / Übungen zu Stochastische Prozesse | Karl-Theodor Sturm |
|
20151 611300702 Übung SWS |
Termine: |
Do 10-12 | SemR 0.008, Endenicher Allee 60
| |
Do 12-14 | SemR 0.011, Endenicher Allee 60
| |
Fr 14-16 | SemR 0.008, Endenicher Allee 60
| |
Do 14-16 | SemR 0.008, Endenicher Allee 60
| |
|
Link to Basis |
|
V4F1 | Stochastic Analysis | Andreas Eberle |
|
20151 611500701 Vorlesung SWS |
Termine: |
Di 12-14 | Kleiner Hörsaal, Wegelerstr. 10
| |
Do 12-14 | Kleiner Hörsaal, Wegelerstr. 10
| |
|
Link to Basis |
|
V4F1 | Exercises to Stochastic Analysis | Andreas Eberle |
|
20151 611700701 Übung SWS |
Termine: |
Mo 12-14 | SemR 0.011, Endenicher Allee 60
| |
Mi 16-18 | SemR 0.006, Endenicher Allee 60
| |
|
Link to Basis |
|
V5F4 | Selected Topics in Stochastic Analysis - Introduction to Optimal Transport and Applications | Matthias Erbar |
|
20151 611500709 Vorlesung SWS |
Termine: |
Mo 08-10 | SemR 1.008, Endenicher Allee 60
| |
|
Literatur: |
References: • C. Villani, Topics in optimal transportation • C. Villani, Optimal transport, old and new • L. Ambrosio, N. Gigli, A user’s guide to optimal transport • F. Otto, The geometry of dissipative evolution equations: The porous medium equation, article • K.-Th. Sturm, The geometry of metric measure spaces, article
|
Bemerkung: |
The optimal transport problem has a long history dating back to Monge in the 18th century. In modern terms the problem is, given two probability distributions to find a transport map pushing one forward to the other that minimizes the total transport cost. In the last two decades the theory has received new attention and seen an enormous development. Striking connections to a number of mathematical fields have been established ranging from probability and economics to PDE and Riemannian geometry, where optimal transport is used as a powerful and versatile tool. In the first part of the lecture we will consider the optimal transport problem in a general setting and cover the beautiful theory leading to existence and characterization of solutions. The second part of the lecture will give an introduction to some recent applications of optimal transport. Possible topics include: • Otto’s geometric interpretation of evolution PDEs: Heat and porous medium equations e.g. as gradient flows in the space of probability measures, Theory of gradient flows in metric spaces • Geometry of singular spaces: How to define a notion of Ricci curvature lower bounds for metric spaces equipped with a measure using optimal transport and properties of such spaces • Using optimal transport to prove geometric and functional inequalities, e.g. isoperimetry and concentration • Variants of the transport problem Prerequisites: A solid background in measure theory is desirable. Some basic knowledge of Riemannian geometry and PDE will be helpful but is not strictly required.
|
Link to Basis |
|