Oberseminar
In each semester we host an oberseminar with topics from mathematical imaging, inverse problems, convex optimization, machine learning and other topics.
Currently the seminar takes place tuesdays from 10:00 to 12:00 in MZH 5450.
Wintersemester 2026
| Date |
Speaker |
Topic |
|
20.10.2026 (10:00 - 10:30)
|
Bikram Adhikary
|
Auxiliary Function Methods for Non-convex Multi-objective Optimization
|
|
20.10.2026 (10:45 - 11:45)
|
Carl Wölper
|
Analysis of Two-Step Methods in Multispectral CT
|
|
27.10.2026
|
Francis Nwawuru
|
Curvature-Adaptive Preconditioned Accelerated Predictor–Corrector Method for Composite Optimization
|
|
03.11.2026
|
Sebastian Banert
|
|
|
10.11.2026
|
Jürgen Jeschke
|
Attenuation Modelling for Multispectral Computed Tomography
|
|
17.11.2026
|
Anakha Ajayakumar
|
|
|
24.11.2026
|
Dennis Oestmann
|
|
|
01.12.2026
|
Giacomo Mozzone
|
|
|
15.12.2026
|
Minoo Daneshmandi
|
|
|
05.01.2027
|
Dirk Lorenz
|
Data Adapted Diagonal Frame Deompositions
|
Previous semesters
Sommersemester 2026
| Date |
Speaker |
Topic |
|
10.06.2026
|
Pascal Fernsel
|
|
|
16.06.2026
|
Jürgen Jeschke
|
|
|
24.06.2026
|
Sebastian Banert
|
|
|
01.07.2026
|
Felix Schneppe
|
|
|
08.07.2026
|
Nina Öhlckers
|
|
Sommersemester 2025
| Date |
Speaker |
Topic |
|
23.04.2025
|
Nina Öhlckers |
|
|
30.04.2025
|
Jürgen Jeschke |
Multispectral Computer Tomography
|
|
07.05.2025
|
Felix Schneppe |
Adjoint mismatch calculation |
|
14.05.2025
|
Sebastian Banert |
Frugal splitting |
|
28.05.2025
|
Dirk Lorenz |
Bilevel learning of regularization of inverse problems |
|
11.06.2025
|
Marcel Brettmacher |
Multimodal data fusion using image registration
|
|
02.07.2025
|
Greeshma Tadana |
Discretization of inverse problems
|
Wintersemester 2024
| Date |
Speaker |
Topic |
|
07.11.2024
|
Jürgen Jeschke |
Generalized Modulo Operators
|
|
14.11.2024
|
Annine Duclaire Kenne |
Machine Learning and climate change
|
|
05.12.2024
|
Jonas Bresch |
Denoising of Manifold-Valued Data by Relaxed Regularization
|
|
12.12.2024
|
|
|
|
16.01.2025
|
Clemens Arndt |
Analytic Deep Prior: Deep Image Prior formulated as a bilevel variational minimization problem
|
|
30.01.2025
|
Oskar Bircks |
Learning to optimize
|
|
06.02.2025
|
Pascal Fernsel |
Convergence Properties of Score-Based Models For Linear Inverse Problems Using Graduated Optimisation
|
|
20.02.2025
|
Markus Haltmeier |
Derivative-Free iterative One-Step Reconstruction for Multispectral CT
|
Sommersemester 2024
| Date |
Speaker |
Topic |
| 22.04.2024 |
Lionel Tondji |
Adaptive Bregman-Kaczmarz |
| 29.04.2024 |
Sebastian Banert |
Algorithms with learned deviations |
| 06.05.2024 |
Andreas Hauptmann |
Learned reconstruction methods and convergent regularization: linear plug-and-play denoiser |
| 13.05.2024 |
Dirk Lorenz |
The inertial Levenberg-Marquardt method for inverse problems |
| 20.05.2024 |
|
No seminar talk planned |
| 27.05.2024 |
Maximilian Winkler |
Intro to the SF-TR CT implementation |
| 03.06.2024 |
Felix Schneppe |
Adjoint-free norm estimation |
| 10.06.2024 |
Derick Tanyu |
Delving into Scientific Machine Learning: Solving PDEs and Parameter Identification with TorchPhysics |
| 17.06.2024 |
Nick Harcken |
Tutorium Talk on Optimal Transport |
| 24.06.2024 |
Sally Schiewelbein |
Seminar Talk Blind Source Separation |
Wintersemester 2023
| Date |
Speaker |
Topic |
| 23/11/2023 |
Andrea Ebner |
Regularization with non-linear frame filtering |
| 30/11/2023 |
Nicole Mücke |
How many Neurons do we need? A refined Analysis for Shallow Networks trained with Gradient Descent |
| 07/12/2023 |
|
|
| 14/12/2023 |
Judith Nickel |
Data-driven regularization theory of invertible ResNets for solving inverse problems |
| 21/12/2023 |
|
|
| 11/01/2024 |
|
|
| 18/01/2024 |
|
|
| 25/01/2024 |
|
|
| 01/02/2024 |
|
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