Veranstaltungen

Dienstag, 21.07.2026, 10:15 Uhr (WIAS-406)

Seminar Nichtlineare Optimierung und Inverse Probleme
Prof. Dr. Abderrahim Jourani, Université de Bourgogne, Dijon, Frankreich:
Error bound characterizations of the conical constraint qualification in convex programming
mehr ... Veranstaltungsort
Weierstraß-Institut, Anton-Wilhelm-Amo-Str. 39, 10117 Berlin, 4. Etage, Weierstraß-Hörsaal (Raum: 406)

Abstrakt
This talk deals with error bound characterizations of the conical constraint qualification (CCQ) for convex inequality systems in a Banach space X. We establish necessary and sufficient conditions for a closed convex set S defined by a convex function g to have CCQ. Our results show that these characterizations hold in very special situations. We construct technical examples showing that these characterizations are limited to these situations. We introduce a new condition in terms of the gauge function which allows us to give an error bound characterization of convex nondifferentiable systems and to obtain as a direct consequence different characterizations of the concept of the strong conical hull intersection property (CHIP) for a finite collection of convex sets.

Veranstalter
WIAS Berlin

Mittwoch, 29.07.2026, 14:15 Uhr (WIAS-ESH)

Berliner Oberseminar „Nichtlineare partielle Differentialgleichungen” (Langenbach-Seminar)
Ass. Prof. Quoc Bao Tang, Universität Graz, Österreich:
Global existence and large time behaviour of nonlinear reaction-diffusion systems
mehr ... Veranstaltungsort
Weierstraß-Institut, Anton-Wilhelm-Amo-Str. 39, 10117 Berlin, Erdgeschoss, Erhard-Schmidt-Hörsaal

Weitere Informationen
Oberseminar “Nichtlineare partielle Differentialgleichungen” (Langenbach-Seminar)

Veranstalter
Humboldt-Universität zu Berlin
WIAS Berlin

Dienstag, 04.08.2026, 10:15 Uhr (WIAS-406)

Seminar Nichtlineare Optimierung und Inverse Probleme
Dr. Hendrik Kleikamp, Universität Graz, Österreich:
From reduced bases to U-Nets: Machine Learning for parametric optimal control
mehr ... Veranstaltungsort
Weierstraß-Institut, Anton-Wilhelm-Amo-Str. 39, 10117 Berlin, 4. Etage, Weierstraß-Hörsaal (Raum: 406)

Abstrakt
In this talk, we consider optimal control problems whose dynamics and objective functional depend on parameters. Solving such problems for many parameter values is often computationally prohibitive. To address this challenge, we consider reduced-order models (ROMs) that accelerate computations while retaining rigorous accuracy guarantees, including a posteriori error estimates.

The projection-based reduced basis ROMs considered here can be further accelerated through the incorporation of machine learning techniques. By combining classical model reduction with machine learning, the a posteriori error estimator can be transferred directly to the machine learning predictions. Moreover, the full-order model, reduced basis ROM, and machine learning surrogate can be organized into an adaptive model hierarchy, in which the different models are trained and employed in an adaptive manner.

In the final part of the talk, we present recent work on the use of U-Nets for nonlinear surrogate modeling in problems characterized by slowly decaying Kolmogorov widths, where linear reduced models are known to struggle. To assess their performance, we compare U-Nets with alternative approaches, including autoencoder architectures and parametric decoders, on challenging optimal control problems.

Veranstalter
WIAS Berlin

7. – 11. September 2026 (HUB main building)

Workshop/Konferenz: 17th International Conference on Free Boundary Problems: Theory and Applications 2026
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Humboldt Universität zu Berlin, Unter den Linden 6, 10117 Berlin

Veranstalter
Humboldt-Universität zu Berlin
WIAS Berlin

3. – 6. November 2026 (WIAS-ESH)

Workshop/Konferenz: Stochastic processes with reinforcement
mehr ... Veranstaltungsort
Weierstraß-Institut, Anton-Wilhelm-Amo-Str. 39, 10117 Berlin, Erdgeschoss, Erhard-Schmidt-Hörsaal

Veranstalter
WIAS Berlin