Steven-Marian Stengl

Preprints

1. Stengl, S.-M. (2023). An Alternative Formulation of the Quantum Phase Estimation Using Projection-based Tensor Decompositions. [arXiv]
   [BibTeX]

   @misc{2023_Stengl_Quantumphaseestimation,
     archiveprefix = {arXiv},
     eprint = {2303.05894},
     primaryclass = {quant-ph},
     year = {2023},
     author = {Stengl, Steven-Marian},
     title = {An Alternative Formulation of the Quantum Phase Estimation Using Projection-based Tensor Decompositions}
   }

2. Hintermüller, M., and Stengl, S.-M. On the Convexity of Optimal Control Problems Involving Non-linear PDEs or VIs and Applications to Nash Games. [URL]
   [BibTeX]

   @misc{2020_MichaelStengl_Convexitynashgames,
     url = {https://wias-berlin.de/publications/wias-publ/run.jsp?template=abstract&type=Preprint&year=2020&number=2759},
     author = {Hintermüller, Michael and Stengl, Steven-Marian},
     title = {On the Convexity of Optimal Control Problems Involving Non-linear PDEs or VIs and Applications to Nash Games}
   }

3. Hintermüller, M., and Stengl, S.-M. A Generalized 𝛤-convergence Concept for a Type of Equilibrium Problems. [URL]
   [BibTeX]

   @misc{2021_MichaelStengl_Generalizedgammaconvergence,
     url = {https://wias-berlin.de/publications/wias-publ/run.jsp?template=abstract&type=Preprint&year=2021&number=2879},
     author = {Hintermüller, Michael and Stengl, Steven-Marian},
     title = {A Generalized 𝛤-convergence Concept for a Type of Equilibrium Problems}
   }

4. Stengl, S.-M. Path-following Methods for Generalized Nash Equilibrium Problems. [arXiv]
   [BibTeX]

   @misc{2021_Stengl_Pathfollowingnash,
     archiveprefix = {arXiv},
     eprint = {2110.10627},
     primaryclass = {math.OC},
     author = {Stengl, Steven-Marian},
     title = {Path-following Methods for Generalized Nash Equilibrium Problems}
   }

5. Stengl, S.-M. Combined Regularization and Discretization of Equilibrium Problems and Primal-dual Gap Estimators. [arXiv]
   [BibTeX]

   @misc{2021_Stengl_Regularizationdiscretization,
     archiveprefix = {arXiv},
     eprint = {2110.02817},
     primaryclass = {math.NA},
     author = {Stengl, Steven-Marian},
     title = {Combined Regularization and Discretization of Equilibrium Problems and Primal-dual Gap Estimators}
   }

Full articles

1. Stengl, S.-M., Gelß, P., Klus, S., and Pokutta, S. (2024). Existence and Uniqueness of Solutions of the Koopman–von Neumann Equation on Bounded Domains. Journal of Physics A: Mathematical and Theoretical. DOI: 10.1088/1751-8121/ad6f7d [URL] [arXiv]
   [BibTeX]

   @article{2023_StenglGelssKlusPokutta_Koopmanvonneumann,
     year = {2024},
     journal = {Journal of Physics A: Mathematical and Theoretical},
     doi = {10.1088/1751-8121/ad6f7d},
     url = {https://iopscience.iop.org/article/10.1088/1751-8121/ad6f7d},
     archiveprefix = {arXiv},
     eprint = {2306.13504},
     primaryclass = {math.AP},
     author = {Stengl, Steven-Marian and Gelß, Patrick and Klus, Stefan and Pokutta, Sebastian},
     title = {Existence and Uniqueness of Solutions of the Koopman--von Neumann Equation on Bounded Domains}
   }

2. Gahururu, D., Hintermüller, M., Stengl, S.-M., and Surowiec, T. M. (2022). Generalized Nash Equilibrium Problems with Partial Differential Operators: Theory, Algorithms, and Risk Aversion. In Non-smooth and Complementarity-based Distributed Parameter Systems: Simulation and Hierarchical Optimization (Vol. 172, pp. 145–181). DOI: 10.1007/978-3-030-79393-7_7
   [BibTeX]

   @incollection{2022_GahururuHintermllerStenglSurowiec_GnepPdesRiskaversion,
     year = {2022},
     booktitle = {Non-smooth and Complementarity-based Distributed Parameter Systems: Simulation and Hierarchical Optimization},
     volume = {172},
     pages = {145–181},
     doi = {10.1007/978-3-030-79393-7_7},
     author = {Gahururu, Deborah and Hintermüller, Michael and Stengl, Steven-Marian and Surowiec, Thomas M.},
     title = {Generalized Nash Equilibrium Problems with Partial Differential Operators: Theory, Algorithms, and Risk Aversion}
   }

3. Hintermüller, M., Stengl, S.-M., and Surowiec, T. (2021). Uncertainty Quantification in Image Segmentation Using the Ambrosio–Tortorelli Approximation of the Mumford–Shah Energy. Journal of Mathematical Imaging and Vision, 63(9), 1095–1117. DOI: 10.1007/s10851-021-01034-2 [URL]
   [BibTeX]

   @article{2021_MichaelStenglThomas_Uncertaintysegmentation,
     year = {2021},
     journal = {Journal of Mathematical Imaging and Vision},
     volume = {63},
     number = {9},
     pages = {1095--1117},
     doi = {10.1007/s10851-021-01034-2},
     url = {https://link.springer.com/article/10.1007/s10851-021-01034-2},
     author = {Hintermüller, Michael and Stengl, Steven-Marian and Surowiec, Thomas},
     title = {Uncertainty Quantification in Image Segmentation Using the Ambrosio–Tortorelli Approximation of the Mumford–Shah Energy}
   }