Patrick Gelß
postdoctoral researcher at ZIB since July 2022📬 Contact
office  Room 1356 at ZIB 

gelss (at) zib.de p.gelss (at) fuberlin.de 

homepage  patrickgelss.com 
languages  German and English 
🎓 Academic Background
Jun 2017  Ph.D. in Applied Mathematics at FUB 

Oct 2013  Diploma in Mathematics at FUB 
🔬 Research
Preprints
 Stengl, S.M., Gelß, P., Klus, S., and Pokutta, S. (2023). Existence and Uniqueness of Solutions of the Koopman–von Neumann Equation on Bounded Domains.
[arXiv]
[BibTeX]
 Designolle, S., Iommazzo, G., Besançon, M., Knebel, S., Gelß, P., and Pokutta, S. (2023). Improved Local Models and New Bell Inequalities Via FrankWolfe Algorithms.
[arXiv]
[BibTeX]
 Gelß, P., Issagali, A., and Kornhuber, R. (2023). Fredholm Integral Equations for Function Approximation and the Training of Neural Networks.
[arXiv]
[BibTeX]
 Gelß, P., Klein, R., Matera, S., and Schmidt, B. (2023). Quantum Dynamics of Coupled Excitons and Phonons in Chainlike Systems: Tensor Train Approaches and Higherorder Propagators.
[arXiv]
[BibTeX]
 Gelß, P., Klus, S., Shakibaei, Z., and Pokutta, S. (2022). Lowrank Tensor Decompositions of Quantum Circuits.
[arXiv]
[BibTeX]
 Gelß, P., and Schütte, C. (2018). Tensorgenerated Fractals  Using Tensor Decompositions for Creating Selfsimilar Patterns.
[arXiv]
[BibTeX]
Full articles
 Riedel, J., Gelß, P., Klein, R., and Schmidt, B. (2023). WaveTrain: A Python Package for Numerical Quantum Mechanics of Chainlike Systems Based on Tensor Trains. The Journal of Chemical Physics, 158(16), 164801.
DOI: 10.1063/5.0147314
[URL]
[arXiv]
[BibTeX]
 Gelß, P., Klein, R., Matera, S., and Schmidt, B. (2022). Solving the Timeindependent Schrödinger Equation for Chains of Coupled Excitons and Phonons Using Tensor Trains. The Journal of Chemical Physics, 156, 024109.
DOI: 10.1063/5.0074948
[URL]
[arXiv]
[BibTeX]
 Gelß, P., Klus, S., Schuster, I., and Schütte, C. (2021). Feature Space Approximation for Kernelbased Supervised Learning. KnowledgeBased Systems, 221, 106935.
DOI: 10.1016/j.knosys.2021.106935
[URL]
[arXiv]
[BibTeX]
 Klus, S., Gelß, P., Nüske, F., and Noé, F. (2021). Symmetric and Antisymmetric Kernels for Machine Learning Problems in Quantum Physics and Chemistry. Machine Learning: Science and Technology, 2(4), 18958.
DOI: 10.1088/26322153/ac14ad
[URL]
[arXiv]
[BibTeX]
 Nüske, F., Gelß, P., Klus, S., and Clementi, C. (2021). Tensorbased Computation of Metastable and Coherent Sets. Physica D: Nonlinear Phenomena, 427, 133018.
DOI: 10.1016/j.physd.2021.133018
[URL]
[arXiv]
[BibTeX]
 Gelß, P., Klus, S., Eisert, J., and Schütte, C. (2019). Multidimensional Approximation of Nonlinear Dynamical Systems. Journal of Computational and Nonlinear Dynamics, 14(6), 25094.
DOI: 10.1115/1.4043148
[URL]
[arXiv]
[BibTeX]
 Klus, S., and Gelß, P. (2019). Tensorbased Algorithms for Image Classification. Algorithms, 12(11), 240.
DOI: 10.3390/a12110240
[URL]
[arXiv]
[BibTeX]
 Gelß, P., Klus, S., Matera, S., and Schütte, C. (2017). Nearestneighbor Interaction Systems in the Tensortrain Format. Journal of Computational Physics, 341, 140–162.
DOI: 10.1016/j.jcp.2017.04.007
[URL]
[arXiv]
[BibTeX]
 Klus, S., Gelß, P., Peitz, S., and Schütte, C. (2017). Tensorbased Dynamic Mode Decomposition. Nonlinearity, 31(7), 3359.
DOI: 10.1088/13616544/aabc8f
[URL]
[arXiv]
[BibTeX]
 Gelß, P., Matera, S., and Schütte, C. (2016). Solving the Master Equation without Kinetic Monte Carlo  Tensor Train Approximations for a CO Oxidation Model. Journal of Computational Physics, 314, 489–502.
DOI: 10.1016/j.jcp.2016.03.025
[URL]
[BibTeX]
 Mossner, M., Jann, J.C., Wittig, J., Nolte, F., Fey, S., Nowak, V., Obländer, J., Pressler, J., Palme, I., Xanthopoulos, C., Boch, T., Metzgeroth, G., Röhl, H., Witt, S. H., Dukal, H., Klein, C., Schmitt, S., Gelß, P., Platzbecker, U., … Nowak, D. (2016). Mutational Hierarchies in Myelodysplastic Syndromes Dynamically Adapt and Evolve Upon Therapy Response and Failure. Blood, 128(9), 1246–1259.
DOI: 10.1182/blood201511679167
[URL]
[BibTeX]
💬 Talks and posters
Conference and workshop talks
 Sep 2022
 Workshop on Advances in Classical and Quantum Algorithms ..., Tokyo / Fukuoka
 Jun 2022
 Conference of the International Linear Algebra Society
 May 2022
 Workshop on Quantum Algorithms and Applications, Brussels
 Dec 2019
 Mathematics of Deep Learning
 Mar 2019
 Annual Meeting of the International Association of Applie...
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Research seminar talks
 Oct 2022
 Tensor Learning Team Seminar
👨🏫 Teaching
 summer 2022
 Lecturer for highdimensional discretization at FUB
 winter 2021
 Tutor for functional analysis at FUB
 summer 2020
 Tutor for dynamical systems at FUB
 winter 2019
 Lecturer for functional analysis at FUB
 summer 2019
 Lecturer for tensor decompositions and their applications at FUB
 winter 2018
 Tutor for functional analysis at FUB