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Oberseminar

In jedem Semester findet wöchentlich unser Oberseminar statt. Die Vortragenden sind Mitglieder des Fachbereichs Mathematik, die über ihre aktuellen Forschungsergebnisse berichten sowie Gäste der Arbeitsgruppen.
Seit der Gründung des Mathematischen Instituts für Maschinelles Lernen und Data Science findet sowohl ein Seminar in Ingolstadt, als auch eines in Eichstätt statt.

Alle Interessierten sind herzlich eingeladen!

Informationen, Themen und Ansprechpartner des Seminars finden Sie hier:

Oberseminar Ingolstadt
Kolloquium Eichstätt

Vergangene Programme

Programm Sommersemester 2022

Je nach Sprecher werden die Vorträge im Sommersemester im Raum KGA-303 oder über Zoom stattfinden (s. Ankündigungsmails).

  • 03.05.2022: Christian Kümmerle, "Dictionary-Sparse Recovery From Heavy-Tailed Measurements"
  • 17.05.2022: Günther Wirsching, "Quantum-Inspired Uncertainty Quantification"
  • 24.05.2022: Laura Thesing, "Which networks can be learned by an algorithm? - Expressivity meets Turing in Deep Learning"
  • 14.06.2022: Yizhe Zhu, "Non-backtracking spectral clustering in sparse hypergraphs"
  • 21.06.2022: Axel Böhm, "On min-max problems and finding weak Minty solutions"
  • 23.06.2022: (Gemeinsames KU-LMU-TUM Seminar)
  • 28.06.2022: Rishabh Dudeja, "Computational Lower Bounds for Tensor PCA"
  • 12.07.2022: Hung-Hsu Chou, "Generalization and Magnification of Implicit Regularization"
  • 21.07.2022: (Gemeinsames KU-LMU-TUM Seminar)
  • 04.08.2022: (Gemeinsames KU-LMU-TUM Seminar)
  • 09.09.2022: Hrushikesh Mhaskar, "Kernel based approximation"

Programm Wintersemester 2021/2022

Aufgrund der aktuellen Pandemie-Situation werden die Vorträge im Sommersemester bis auf Weiteres wieder über Zoom stattfinden.

  • 19.10.2021: Organisatorisches Treffen
  • 26.10.2021: Hidde Schönberger, "Fractional Integrals and Supremals: Characterization of Lower Semicontinuity and Relaxation"
  • 02.11.2021: Andrei Caragea, "Hierarchical exponential Riesz bases"
  • 09.11.2021: Valerio Pagliari, "A homogenization problem inspired by high-contrast materials"
  • 16.11.2021: Johannes Krebs, "Statistical topological data analysis"
  • 23.11.2021: Jona Lelmi, "Large data limit for the MBO scheme for data clustering: Gamma-convergence of the thresholding energies"
  • 25.11.2021: Dominik Stöger, "Small random initialization is akin to spectral learning: Optimization and generalization guarantees for overparameterized low-rank matrix reconstruction" + Felix Voigtländer, "The universal approximation theorem for complex-valued neural networks" (Gemeinsames KU-LMU-TUM Seminar)
  • 07.12.2021: Ekkehard Schnoor, "Generalization Error Bounds for Iterative Recovery Algorithms Unfolded as Neural Networks"
  • 14.12.2021: Weihnachtsfeier der KU -> Abgesagt...
  • 11.01.2022: Martin Genzel, "The Separation Capacity of Random Neural Networks"
  • 18.01.2022: Konstantin Riedl, "Mean-Field Law Global Convergence of Consensus-Based Optimization"
  • 20.01.2022: Cristina Cipriani, "A Mean-Field Optimal Control Approach to the Training of NeurODEs" + Olga Graf, "One-bit unlimited sampling" (Gemeinsames KU-LMU-TUM Seminar)
  • 25.01.2022: Frank Filbir, "Shift Invariant Spaces related to the Special Affine Fourier Transform"
  • 01.02.2022: Hans-Christian Jung, "Learning interesting probability distributions"
  • 24.02.2022: Adalbert Fono, "Limitations of Deep Learning on Digital Hardware" + Sohir Maskey, "Stability and Generalization Capabilities of Message Passing Graph Neural Networks" (Gemeinsames KU-LMU-TUM Seminar)
  • 01.03.2022: Theophil Trippe, "Learning to Invert Defocus Blur: A Data-Driven Approach to the 'Helsinki Deblur Challenge'"
  • 29.03.2022: Marco Morandotti, "Minimisers of the Canham-Helfrich functional in the space of generalised Gauss graphs"

Programm Sommersemester 2021

Aufgrund der aktuellen Pandemie-Situation werden die Vorträge im Sommersemester bis auf Weiteres wieder über Zoom stattfinden.

  • 20.04.2021: Organisatorisches Treffen
  • 22.04.2021: Dae Gwan Lee, "A quantitative approximation result for complex-valued neural networks and applications" + Johannes Maly, "Gradient Descent for Deep Matrix Factorization: Dynamics and Implicit Bias towards Low Rank" (Gemeinsames KU-LMU-TUM Seminar)
  • 04.05.2021: Dominik Stöger, "Understanding overparameterization in low-rank matrix recovery and generative adversarial networks"
  • 11.05.2021: Hung-Hsu Chou, "Overparameterization and generalization error: weighted trigonometric interpolation"
  • 18.05.2021: Dominik Engl, "Theories for incompressible strings and rods: a rigorous derivation via Γ-convergence"
  • 01.06.2021: Ursula Molter, "Tiles, Multi-tiles, Riesz bases of exponentials and the Bohr topology"
  • 15.06.2021: Claudio Verdun, "How to impute data and complete matrices if you must"
  • 22.06.2021: Gabin Maxime Nguegnang, "Convergence of Gradient Descent in Learning Deep Linear Networks"
  • 29.06.2021: Antonella Ritorto, "Asymptotic analysis of rigidity constraints modeling fiber-reinforced composite"
  • 13.07.2021: Carolin Kreisbeck, "Nonlocal variational problems: Structure-preservation during relaxation?"
  • 20.07.2021: Patrik Hammer, "Universal approximation results in the theory of neural networks"

Programm Wintersemester 2020/2021

  • 10.11.2020: Johannes Maly, "Gradient Descent for Deep Matrix Factorizations"
  • 08.12.2020: Sjoerd Dirksen, "Covariance estimation under one-bit quantization"
  • 22.12.2020: Javier Cueto, "Vector Variational Problems based on Fractional and Nonlocal Gradients. Applications to Solid Mechanics"
  • 12.01.2021: Dmitry Yarotsky, "Approximations with deep neural networks"
  • 26.01.2021: Timo Klock, "Deep neural networks adapt to intrinsic dimensionality beyond the data domain"
  • 02.02.2021: Diyora Salimova, "Space-time deep neural network approximations for high-dimensional PDEs"
  • 16.02.2021: Michael Rauchensteiner, "Stable Recovery of Entangled Weights: Towards Robust
    Identification of Deep Neural Networks"

Programm Sommersemester 2020

  • 09.04.2020: Dr. Michael Speckbacher
  • 07.05.2020: Dr. Wolfgang Erb (KU Eichstätt-Ingolstadt), Anisotropic N-term approximation with Gaussians
  • 26.05.2020: Prof. Radu Balan (University of Maryland, USA), Permutation invariant representations and graph deep learning - Part 1
  • 01.06.2020: Public Holiday
  • 08.06.2020: Prof. Marcin Bownik (University of Oregon, USA), Exponential frames and syndetic Riesz sequences, 6:00 pm (Time in Germany)
  • 15.06.2020: Prof. Radu Balan (University of Maryland, USA), Permutation invariant representations and graph deep learning - Part 2
  • 22.06.2020: Prof. Philippe Jaming (Université de Bordeaux, France), Mobile and diffusive sampling
  • 06.07.2020: Prof. Shahaf Nitzan (Georgia Institute of Technology, USA), Uncertainty Principles for Fourier Multipliers
  • 20.07.2020: Franziska Schlamp (KU Eichstätt-Ingolstadt), Presentation about internship at Airbus

Programm Wintersemester 2019/2020

  • 04.11.2019: Franziska Schlamp (KU Eichstätt-Ingolstadt), Minimizing power loss for automotive electrical engines
  • 11.11.2019: Dr. Dae Gwan Lee (KU Eichstätt-Ingolstadt), A review of combining Riesz bases of intervals - Part I
  • 14.11.2019: Andrei Caragea (KU Eichstätt-Ingolstadt), A review of combining Riesz bases of intervals - Part II
  • 20.11.2019: Dr. Peter Jung (TU Berlin), Robust Recovery of Sparse Nonnegative Weights from Mixtures of Positive-Semidefinite Matrices
  • 25.11.2019: Prof. Radha Ramakrishnan (Indian Institute of Technology Madras), Stable set of sampling in shift invariant spaces with multiple generators
  • 02.12.2019: Ronald Gerbig (Airbus Defense and Space), Introduction to Airborne Radar I
  • 09.12.2019: Ronald Gerbig (Airbus Defense and Space), Introduction to Airborne Radar II
  • 20.01.2020: Prof. Boris Bittner (FHW Schweinfurt), Non-separated sampling sequences
  • 27.01.2020: Carolin Strößner (KU Eichstätt-Ingolstadt), Analysis of a network model for sediment flow movements
  • 10.03.2020: Franziska Schlamp (KU Eichstätt-Ingolstadt), Description of the spectrum of a dual inverter

Programm Sommersemester 2019

Programm Wintersemester 2018/2019

Programm Sommersemester 2018

  • 18. April 2018: Dr. Friedrich Philipp (KU Eichstätt), Frame Orbits of Linear Operators
  • 24. April 2018: Prof. Dr. Felix Krahmer (TU München), On the connection between A/D conversion and the roots of Chebyshev polynomials
  • 2. Mai 2018: Prof. Dr. Peter Singer (Technische Hochschule Ingolstadt), Characerization of Fourier and Wavelet Transforms by their scaling behaviour
  • 9. Mai 2018: Dr. Friedrich Philipp (KU Eichstätt), Frame Orbits of Linear Operators: Proofs
  • 16. Mai 2018: Schwester Johanna (KU Eichstätt), Classification of subfactors: An overview
  • 23. Mai 2018: Stefan Pautze, Cyclotomic Aperiodic Substitution Tilings
  • 29. Mai 2018: Ilya Krishtal (Northern Illinois University),Dynamical Sampling and Phaseless Reconstruction
  • 30. Mai 2018: Philipp Petersen (TU Berlin), Neural Networks and Partial Differential Equations: Challenges and Opportunities
  • 13. Juni 2018: Nicki Holighaus (Institut für Schallforschung), Aspects of warped time-frequency representations

Programm Wintersemester 2017/2018

  • 21.11.2017: H. Bayindir, Trigonometric Approximation
  • 05.12.2017: Prof. Hans-Peter Blatt (KU Eichstätt-Ingolstadt), Potential Theoretical Aspects in Constructive Function Theory
  • 12.12.2017: Prof. Jeffrey Hogan (Univ. of Newcastle), On the Search for Multidimensional Wavelets (Abstract)
  • 19.12.2017: Prof. Götz E. Pfander (KU Eichstätt-Ingolstadt), Boundedness of Pseudodifferential Operators on Modulation Spaces (Abstract)
  • 09.01.2018: Dr. Nada Sissouno (TU München), Recovery of dynamical systems using compressed sensing
  • 16.01.2018: Dr. Friedrich Philipp (KU Eichstätt-Ingolstadt), On the Jordan Structure of Finite Rank Perturbations of Linear Relations (Abstract)
  • 23.01.2018: Andrei Caragea (KU Eichstätt-Ingolstadt), Spaceability of subsets of Banach spaces
  • 30.01.2018: Dr. Volker Pohl (TU München), On the possibility to calculate the Hilbert Transform on digital computers
  • 06.02.2018: Dr. Friedrich Philipp (KU Eichstätt-Ingolstadt), Sums of frame sequences
  • 13.02.2018: Amit Chaulwar (CARISSMA, Technische Hochschule Ingolstadt), Hybrid Statistical Learning Methods for the Embedded-Implementation of Vehicle Safety Functions (Abstract) 
  • 13.02.2018: Parthasarathy Nadarajan (CARISSMA, Technische Hochschule Ingolstadt), Efficient Design and Validation of Vehicle Safety Systems based on Predicted Occupancy Grids and Statistical Learning (Abstract)

Programm Sommersemester 2017

  • 09.05.2017: Weiqi Zhou (KU Eichstätt-Ingolstadt), Irregular orthonormal Gabor basis on prime dimensions
  • 16.05.2017: Dr. Dae Gwan Lee (KU Eichstätt-Ingolstadt), Extra invariance of Gabor spaces and the Balian-Low theorem
  • 23.05.2017: Andrei Caragea (KU Eichstätt-Ingolstadt), Additional invariance of Gabor spaces generated by ZxPZ and continuity of Zak transform
  • 08.06.2017: Andrei Caragea (KU Eichstätt-Ingolstadt), The classical Balian-Low theorem and additional time-frequency shifts in the Gabor space over ZxPZ
  • 20.06.2017: Dr. Friedrich Philipp (KU Eichstätt-Ingolstadt), Dynamical sampling on finite index sets
  • 27.06.2017: Prof. René Grothmann (KU Eichstätt-Ingolstadt), Some problems in approximation theory
  • 29.06.2017: Andrei Caragea (KU Eichstätt-Ingolstadt), Additional time-frequency shift by (1/2, 0) for Gabor spaces over Zx3Z
  • 11.07.2017: Andrei Caragea (KU Eichstätt-Ingolstadt), Finite uncertainty product and additional rational time-frequency shifts for a Gabor space
  • 25.07.2017: Dr. Van Kien Nguyen (Friedrich-Schiller-Universität Jena), Besov spaces of dominating mixed smoothness and Gelfand numbers

    Old webpage:
    https://www.ku.de/mgf/mathematik/lehrstuhlwissenschaftlichesrechnen/seminar/
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