Preprints

• N. Derevianko. Recovery of rational functions via Hankel pencil method and sensitivities of the poles , preprint 2024.

• N. Derevianko and G. Plonka. Differential approximation of the Gaussian by short cosine sums with exponential error decay, preprint 2023.

• A. González-Sanz, M. Groppe, and A. Munk. Nonlinear Inverse Optimal Transport: Identifiability of the Transport Cost from its Marginals and Optimal Values, preprint 2023.

• A. González-Sanz and S. Hundrieser. Weak Limits for Empirical Entropic Optimal Transport: Beyond Smooth Costs, preprint 2023.

• M. Groppe and S. Hundrieser. Lower Complexity Adaptation for Empirical Entropic Optimal Transport, preprint 2023.

• S. Hundrieser, B. Eltzner, and S. Huckemann. A Lower Bound for Estimating Fréchet Means, preprint 2024.

• L. Lammers, D. Tran Van, and S. Huckemann. Sticky Flavors, preprint 2023.

• T. G. Nies, T. Staudt, and A. Munk. Transport Dependency: Optimal Transport Based Dependency Measures, preprint 2021.

• G. Plonka and Y. Riebe. MOCCA: A Fast Algorithm for Parallel MRI Reconstruction Using Model Based Coil Calibration, preprint 2024.

• D. Schuhmacher and L. Wirth. Assignment Based Metrics for Attributed Graphs, preprint 2023.
  • D. Schuhmacher and L. Wirth. Stein's Method for Spatial Random Graphs, preprint 2024.
  • T. Staudt and S. Hundrieser. Convergence of Empirical Optimal Transport in Unbounded Settings, preprint 2023.
  • T. Staudt, S. Hundrieser, and A. Munk. On the Uniqueness of Kantorovich Potentials, preprint 2022.
  • A. Sturm and M. Wemheuer. A Central Limit Theorem for Functions on Weighted Sparse Inhomogeneous Random Graphs, preprint 2024.
  • L. Suchan, H. Li and A. Munk. A scalable clustering algorithm to approximate graph cuts, preprint 2023.
  • L. Suchan, H. Li and A. Munk. Distributional limits of graph cuts on discretized grids, preprint 2024.