@inbook{56201,
  author       = {{Biehler, Rolf and Hoffmann, Max}},
  booktitle    = {{Konzepte und Studien zur Hochschuldidaktik und Lehrerbildung Mathematik}},
  isbn         = {{9783662639474}},
  issn         = {{2197-8751}},
  publisher    = {{Springer Berlin Heidelberg}},
  title        = {{{Fachwissen als Grundlage fachdidaktischer Urteilskompetenz – Beispiele für die Herstellung konzeptueller Bezüge zwischen fachwissenschaftlicher und fachdidaktischer Lehre im gymnasialen Lehramtsstudium}}},
  doi          = {{10.1007/978-3-662-63948-1_4}},
  year         = {{2022}},
}

@inbook{56203,
  author       = {{Hoffmann, Max and Biehler, Rolf}},
  booktitle    = {{Konzepte und Studien zur Hochschuldidaktik und Lehrerbildung Mathematik}},
  isbn         = {{9783658340667}},
  issn         = {{2197-8751}},
  publisher    = {{Springer Fachmedien Wiesbaden}},
  title        = {{{Schnittstellenaufgaben in der Analysis I zur Verknüpfung von Schul- und Hochschulmathematik – Aufgabenbeispiel und Ergebnisse einer Evaluationsstudie}}},
  doi          = {{10.1007/978-3-658-34067-4_20}},
  year         = {{2022}},
}

@inbook{43231,
  author       = {{Podworny, Susanne and Frischemeier, Daniel and Biehler, Rolf}},
  booktitle    = {{Statistics for Empowerment and Social Engagement}},
  isbn         = {{9783031207471}},
  publisher    = {{Springer International Publishing}},
  title        = {{{Civic Statistics for Prospective Teachers: Developing Content and Pedagogical Content Knowledge Through Project Work}}},
  doi          = {{10.1007/978-3-031-20748-8_15}},
  year         = {{2022}},
}

@inbook{43230,
  author       = {{Frischemeier, Daniel and Podworny, Susanne and Biehler, Rolf}},
  booktitle    = {{Statistics for Empowerment and Social Engagement}},
  isbn         = {{9783031207471}},
  pages        = {{199--236}},
  publisher    = {{Springer International Publishing}},
  title        = {{{Data Visualization Packages for Non-inferential Civic Statistics in High School Classrooms}}},
  doi          = {{10.1007/978-3-031-20748-8_9}},
  year         = {{2022}},
}

@inproceedings{39062,
  author       = {{Liebendörfer, Michael and Profeta, Angelo and Krämer, Sandra and Schlüter, Sarah and Becher, Silvia and Biehler, Rolf and Mai, Tobias and Schmitz, Angela}},
  location     = {{Bozen-Bolzano, Italy}},
  title        = {{{Enriching videos with interactive questions to enhance students’ cognitive activity: concept and implementation}}},
  year         = {{2022}},
}

@inproceedings{39064,
  author       = {{Podworny, Susanne and Fleischer, Franz Yannik and Stroop, Dietlinde and Biehler, Rolf}},
  location     = {{Bozen-Bolzano, Italy}},
  title        = {{{An example of rich, real and multivariate survey data for use in school}}},
  year         = {{2022}},
}

@inproceedings{56251,
  abstract     = {{<jats:p>Statistical reasoning and the confrontation with first ideas of uncertainty can already be enhanced in primary school. A challenge is how to relate theoretical-combinatorial aspects to empirical frequency aspects, given that fraction concepts are usually not available at primary school. In the frame of a Design Based Research approach we have designed and realized a teaching sequence consisting of seven lessons to develop statistical reasoning about uncertainty of grade 4 students (age 10-11). To supervise their learning processes we collected data on different levels: (a) written pre/post-tests, (b) working notes after each lesson and (c) interviews after the teaching unit. In this paper we will mainly present the design of teaching unit and first results from the analysis of pre- and posttests.</jats:p>}},
  author       = {{Frischemeier, Daniel and Biehler, Rolf}},
  booktitle    = {{Decision Making Based on Data Proceedings IASE 2019 Satellite Conference}},
  publisher    = {{International Association for Statistical Education}},
  title        = {{{Design of a teaching unit to develop primary school students ́ reasoning about uncertainty in multi-step chance experiments}}},
  doi          = {{10.52041/srap.19304}},
  year         = {{2022}},
}

@misc{64268,
  author       = {{Kuit, Job}},
  title        = {{{Plancherel theory on real spherical spaces}}},
  year         = {{2022}},
}

@article{64570,
  author       = {{Olbrich, Martin and Palmirotta, Guendalina}},
  issn         = {{0232-704X}},
  journal      = {{Annals of Global Analysis and Geometry}},
  number       = {{1}},
  publisher    = {{Springer Science and Business Media LLC}},
  title        = {{{Delorme’s intertwining conditions for sections of homogeneous vector bundles on two- and three-dimensional hyperbolic spaces}}},
  doi          = {{10.1007/s10455-022-09882-w}},
  volume       = {{63}},
  year         = {{2022}},
}

@article{64571,
  abstract     = {{We study the Fourier transform for compactly supported distributional sections of complex homogeneous vector bundles on symmetric spaces of non-compact type $X = G/K$. We prove a characterisation of their range. In fact, from Delorme's Paley-Wiener theorem for compactly supported smooth functions on a real reductive group of Harish-Chandra class, we deduce topological Paley-Wiener and Paley-Wiener-Schwartz theorems for sections.}},
  author       = {{Olbrich, Martin and Palmirotta, Guendalina}},
  journal      = {{Journal of Lie theory}},
  number       = {{2}},
  pages        = {{53----384}},
  publisher    = {{Heldermann Verlag}},
  title        = {{{A topological Paley-Wiener-Schwartz Theorem for sections of homogeneous vector bundles on $G/K$}}},
  volume       = {{34}},
  year         = {{2022}},
}

@inbook{56202,
  author       = {{Sjuts, Johann}},
  booktitle    = {{Konzepte und Studien zur Hochschuldidaktik und Lehrerbildung Mathematik}},
  isbn         = {{9783658340667}},
  issn         = {{2197-8751}},
  publisher    = {{Springer Fachmedien Wiesbaden}},
  title        = {{{Lehrerbildung als staatliche und gesellschaftliche Aufgabe angesichts gegenwärtiger und zukünftiger Herausforderungen}}},
  doi          = {{10.1007/978-3-658-34067-4_2}},
  year         = {{2022}},
}

@article{51385,
  author       = {{Hilgert, Joachim and Weich, Tobias and Bux, K.-U.}},
  journal      = {{J. of Spectral Theory}},
  pages        = {{659--681}},
  title        = {{{Poisson transforms for trees of bounded degree}}},
  volume       = {{12}},
  year         = {{2022}},
}

@unpublished{44537,
  author       = {{Burban, Igor and Alfes-Neumann, C. and Raum, M.}},
  title        = {{{A classification of polyharmonic Maaß forms via quiver representations}}},
  year         = {{2022}},
}

@article{24169,
  author       = {{Nüske, Feliks and Gelß, Patrick and Klus, Stefan and Clementi, Cecilia}},
  issn         = {{0167-2789}},
  journal      = {{Physica D: Nonlinear Phenomena}},
  title        = {{{Tensor-based computation of metastable and coherent sets}}},
  doi          = {{10.1016/j.physd.2021.133018}},
  year         = {{2021}},
}

@article{24170,
  author       = {{Klus, Stefan and Gelß, Patrick and Nüske, Feliks and Noé, Frank}},
  issn         = {{2632-2153}},
  journal      = {{Machine Learning: Science and Technology}},
  title        = {{{Symmetric and antisymmetric kernels for machine learning problems in quantum physics and chemistry}}},
  doi          = {{10.1088/2632-2153/ac14ad}},
  year         = {{2021}},
}

@article{21195,
  author       = {{Goelz, Christian and Mora, Karin and Stroehlein, Julia Kristin and Haase, Franziska Katharina and Dellnitz, Michael and Reinsberger, Claus and Vieluf, Solveig}},
  journal      = {{Cognitive Neurodynamics}},
  title        = {{{Electrophysiological signatures of dedifferentiation differ between fit and less fit older adults}}},
  doi          = {{10.1007/s11571-020-09656-9}},
  year         = {{2021}},
}

@article{21337,
  abstract     = {{We present a flexible trust region descend algorithm for unconstrained and
convexly constrained multiobjective optimization problems. It is targeted at
heterogeneous and expensive problems, i.e., problems that have at least one
objective function that is computationally expensive. The method is
derivative-free in the sense that neither need derivative information be
available for the expensive objectives nor are gradients approximated using
repeated function evaluations as is the case in finite-difference methods.
Instead, a multiobjective trust region approach is used that works similarly to
its well-known scalar pendants. Local surrogate models constructed from
evaluation data of the true objective functions are employed to compute
possible descent directions. In contrast to existing multiobjective trust
region algorithms, these surrogates are not polynomial but carefully
constructed radial basis function networks. This has the important advantage
that the number of data points scales linearly with the parameter space
dimension. The local models qualify as fully linear and the corresponding
general scalar framework is adapted for problems with multiple objectives.
Convergence to Pareto critical points is proven and numerical examples
illustrate our findings.}},
  author       = {{Berkemeier, Manuel Bastian and Peitz, Sebastian}},
  issn         = {{2297-8747}},
  journal      = {{Mathematical and Computational Applications}},
  number       = {{2}},
  title        = {{{Derivative-Free Multiobjective Trust Region Descent Method Using Radial  Basis Function Surrogate Models}}},
  doi          = {{10.3390/mca26020031}},
  volume       = {{26}},
  year         = {{2021}},
}

@article{21820,
  abstract     = {{<jats:p>The reduction of high-dimensional systems to effective models on a smaller set of variables is an essential task in many areas of science. For stochastic dynamics governed by diffusion processes, a general procedure to find effective equations is the conditioning approach. In this paper, we are interested in the spectrum of the generator of the resulting effective dynamics, and how it compares to the spectrum of the full generator. We prove a new relative error bound in terms of the eigenfunction approximation error for reversible systems. We also present numerical examples indicating that, if Kramers–Moyal (KM) type approximations are used to compute the spectrum of the reduced generator, it seems largely insensitive to the time window used for the KM estimators. We analyze the implications of these observations for systems driven by underdamped Langevin dynamics, and show how meaningful effective dynamics can be defined in this setting.</jats:p>}},
  author       = {{Nüske, Feliks and Koltai, Péter and Boninsegna, Lorenzo and Clementi, Cecilia}},
  issn         = {{1099-4300}},
  journal      = {{Entropy}},
  title        = {{{Spectral Properties of Effective Dynamics from Conditional Expectations}}},
  doi          = {{10.3390/e23020134}},
  year         = {{2021}},
}

@article{16867,
  abstract     = {{In this article, we present an efficient descent method for locally Lipschitz
continuous multiobjective optimization problems (MOPs). The method is realized
by combining a theoretical result regarding the computation of descent
directions for nonsmooth MOPs with a practical method to approximate the
subdifferentials of the objective functions. We show convergence to points
which satisfy a necessary condition for Pareto optimality. Using a set of test
problems, we compare our method to the multiobjective proximal bundle method by
M\"akel\"a. The results indicate that our method is competitive while being
easier to implement. While the number of objective function evaluations is
larger, the overall number of subgradient evaluations is lower. Finally, we
show that our method can be combined with a subdivision algorithm to compute
entire Pareto sets of nonsmooth MOPs.}},
  author       = {{Gebken, Bennet and Peitz, Sebastian}},
  journal      = {{Journal of Optimization Theory and Applications}},
  pages        = {{696--723}},
  title        = {{{An efficient descent method for locally Lipschitz multiobjective optimization problems}}},
  doi          = {{10.1007/s10957-020-01803-w}},
  volume       = {{188}},
  year         = {{2021}},
}

@article{16295,
  abstract     = {{It is a challenging task to identify the objectives on which a certain decision was based, in particular if several, potentially conflicting criteria are equally important and a continuous set of optimal compromise decisions exists. This task can be understood as the inverse problem of multiobjective optimization, where the goal is to find the objective function vector of a given Pareto set. To this end, we present a method to construct the objective function vector of an unconstrained multiobjective optimization problem (MOP) such that the Pareto critical set contains a given set of data points with prescribed KKT multipliers. If such an MOP can not be found, then the method instead produces an MOP whose Pareto critical set is at least close to the data points. The key idea is to consider the objective function vector in the multiobjective KKT conditions as variable and then search for the objectives that minimize the Euclidean norm of the resulting system of equations. By expressing the objectives in a finite-dimensional basis, we transform this problem into a homogeneous, linear system of equations that can be solved efficiently. Potential applications of this approach include the identification of objectives (both from clean and noisy data) and the construction of surrogate models for expensive MOPs.}},
  author       = {{Gebken, Bennet and Peitz, Sebastian}},
  journal      = {{Journal of Global Optimization}},
  pages        = {{3--29}},
  publisher    = {{Springer}},
  title        = {{{Inverse multiobjective optimization: Inferring decision criteria from data}}},
  doi          = {{10.1007/s10898-020-00983-z}},
  volume       = {{80}},
  year         = {{2021}},
}