@article{FischerGerberKopruckietal.2025, author = {Fischer, Kristina and Gerber, Anja and Koprucki, Thomas and Noback, Andres and Reidelbach, Marco and Schrade, Torsten and Thiery, Florian}, title = {Windows on Data: Federating Research Data with FAIR Digital Objects and Linked Open Data}, journal = {2nd Conference on Research Data Infrastructure (CoRDI)}, doi = {10.5281/zenodo.16736222}, year = {2025}, language = {en} } @article{MarcoMarcus2025, author = {Marco, Reidelbach and Marcus, Weber}, title = {From Documentation to Discovery - MaRDMO and the MaRDI Ecosystem}, journal = {2nd Conference on Research Data Infrastructure (CoRDI)}, doi = {10.5281/zenodo.16735889}, year = {2025}, language = {en} } @article{SchemberaWuebbelingShehuetal.2025, author = {Schembera, Bj{\"o}rn and W{\"u}bbeling, Frank and Shehu, Aurela and Biedinger, Christine and Fiedler, Jochen and Reidelbach, Marco and Schmidt, Burkhard and Ferrer, Eloi and Koprucki, Thomas}, title = {FAIR Representation of Mathematical Research Data: MathModDB and MathAlgoDB as Knowledge Graphs for Mathematical Models and Numerical Algorithms}, journal = {2nd Conference on Research Data Infrastructure (CoRDI)}, doi = {10.5281/zenodo.16735911}, year = {2025}, language = {en} } @article{Marco2025, author = {Marco, Reidelbach}, title = {MaRDMO: Future Gateway to FAIR Mathematical Data}, journal = {E-Science-Tage 2025: Research Data Management: Challenges in a Changing World}, doi = {10.11588/heibooks.1652.c23913}, pages = {40 -- 53}, year = {2025}, abstract = {Mathematical research data plays a crucial role across scientific disciplines, yet its documentation and dissemination remain challenging due to the lack of standardized research data management practices. The MaRDMO Plugin addresses these challenges by integrating mathematical models, algorithms, and interdisciplinary workflows into the established framework of the Research Data Management Organiser (RDMO). Built on FAIR principles, MaRDMO enables structured documentation and retrieval of mathematical research data through guided questionnaires. It connects to multiple knowledge graphs, including MathModDB, MathAlgoDB, and the MaRDI Portal. Users can document and search for models, algorithms, and workflows via dynamic selection interfaces that also leverage other sources such as Wikidata. The plugin facilitates the export to the individual MaRDI services, ensuring data quality through automated validation. By embedding mathematical research data management into the widely adopted RDMO platform, MaRDMO represents a significant step toward making mathematical research data more findable, accessible, and reusable.}, language = {en} } @inproceedings{SchemberaWuebbelingKleikampetal.2025, author = {Schembera, Bj{\"o}rn and W{\"u}bbeling, Frank and Kleikamp, Hendrik and Schmidt, Burkhard and Shehu, Aurela and Reidelbach, Marco and Biedinger, Christine and Fiedler, Jochen and Koprucki, Thomas and Iglezakis, Dorothea and G{\"o}ddeke, Dominik}, title = {Towards a Knowledge Graph for Models and Algorithms in Applied Mathematics}, volume = {2331}, booktitle = {Metadata and Semantic Research. MTSR 2024}, publisher = {Springer Nature Switzerland}, address = {Cham}, isbn = {9783031819735}, issn = {1865-0929}, doi = {10.1007/978-3-031-81974-2_8}, pages = {95 -- 109}, year = {2025}, abstract = {Mathematical models and algorithms are an essential part of mathematical research data, as they are epistemically grounding numerical data. To make this research data FAIR, we present how two previously distinct ontologies, MathAlgoDB for algorithms and MathModDB for models, were merged and extended into a living knowledge graph as the key outcome. This was achieved by connecting the ontologies through computational tasks that correspond to algorithmic tasks. Moreover, we show how models and algorithms can be enriched with subject-specific metadata, such as matrix symmetry or model linearity, essential for defining workflows and determining suitable algorithms. Additionally, we propose controlled vocabularies to be added, along with a new class that differentiates base quantities from specific use case quantities. We illustrate the capabilities of the developed knowledge graph using two detailed examples from different application areas of applied mathematics, having already integrated over 250 research assets into the knowledge graph.}, language = {en} } @article{SekulicSchaibleMuelleretal.2025, author = {Sekulic, Ivan and Schaible, Jonas and M{\"u}ller, Gabriel and Plock, Matthias and Burger, Sven and Mart{\´i}nez-Lahuerta, V{\´i}ctor Jos{\´e} and Gaaloul, Naceur and Schneider, Philipp-Immanuel}, title = {Physics-informed Bayesian optimization of expensive-to-evaluate black-box functions}, volume = {6}, journal = {Mach. Learn. Sci. Technol.}, publisher = {IOP Publishing}, doi = {10.1088/2632-2153/ae1f5f}, pages = {040503}, year = {2025}, abstract = {Abstract Bayesian optimization with Gaussian process surrogates is a popular approach for optimizing expensive-to-evaluate functions in terms of time, energy, or computational resources. Typically, a Gaussian process models a scalar objective derived from observed data. However, in many real-world applications, the objective is a combination of multiple outputs from physical experiments or simulations. Converting these multidimensional observations into a single scalar can lead to information loss, slowing convergence and yielding suboptimal results. To address this, we propose to use multi-output Gaussian processes to learn the full vector of observations directly, before mapping them to the scalar objective via an inexpensive analytical function. This physics-informed approach retains more information from the underlying physical processes, improving surrogate model accuracy. As a result, the approach accelerates optimization and produces better final designs compared to standard implementations.}, language = {en} } @inproceedings{SchummelTeichmannGonnermannMueller2025, author = {Schummel, Philip and Teichmann, Malte and Gonnermann-M{\"u}ller, Jana}, title = {Specifying ten roles of using chatgpt in secondary education: a teacher´s perspective}, booktitle = {Proceedings of the European Conference on Information Systems}, year = {2025}, abstract = {ChatGPT can benefit education; however, challenges arise that demand competent and responsible usage. Competence development needs to start in schools, with the teacher being the gatekeeper for integrating it into the teaching process. Existing research suggests that schoolteachers lack specific guidance on integrating ChatGPT into teaching, as current discussions remain high-level and omit specific use cases throughout the entire teaching process. To guide an informed usage, this paper presents the results of a systematic literature review, analyzing 38 selected papers on investigating ChatGPT in schools. This selection is based on rigorously defined criteria, adhering to the PRISMA guidelines, initially screening 1075 papers. The central value of this paper is to aggregate research into ten roles for secondary teachers on using ChatGPT in schools, presenting corresponding use cases throughout the teaching process. Future research validates the ten roles, conducting interviews with teachers to present an exhaustive framework for integrating ChatGPT in schoolteacher practice.}, language = {en} } @inproceedings{KeraPelleritiIshiharaetal.2025, author = {Kera, Hiroshi and Pelleriti, Nico and Ishihara, Yuki and Zimmer, Max and Pokutta, Sebastian}, title = {Computational Algebra with Attention: Transformer Oracles for Border Basis Algorithms}, booktitle = {Proceedings of the Conference on Neural Information Processing Systems}, year = {2025}, language = {en} } @inproceedings{GonnermannMuellerSahlingHaase2025, author = {Gonnermann-M{\"u}ller, Jana and Sahling, Kristina and Haase, Jennifer}, title = {Let's Be Realistic: AI-Recommender Use in a Complex Management Setting}, booktitle = {CHI EA '25: Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems}, doi = {10.1145/3706599.3720131}, year = {2025}, language = {en} } @article{LeinsGonnermannMuellerTeichmann2024, author = {Leins, Nicolas and Gonnermann-M{\"u}ller, Jana and Teichmann, Malte}, title = {Comparing head-mounted and handheld augmented reality for guided assembly}, journal = {Journal on Multimodal User Interfaces}, year = {2024}, language = {en} } @article{GonnermannMuellerKrueger2024, author = {Gonnermann-M{\"u}ller, Jana and Kr{\"u}ger, Jule M.}, title = {Unlocking Augmented Reality Learning Design Based on Evidence From Empirical Cognitive Load Studies—A Systematic Literature Review}, journal = {Journal of Computer Assisted Learning}, year = {2024}, language = {en} } @inproceedings{GłuchTuranNagarajanetal.2025, author = {Głuch, Grzegorz and Turan, Berkant and Nagarajan, Sai Ganesh and Pokutta, Sebastian}, title = {The Good, the Bad and the Ugly: Meta-Analysis of Watermarks, Transferable Attacks and Adversarial Defenses}, booktitle = {Proceedings of the Conference on Neural Information Processing Systems}, year = {2025}, language = {en} } @article{HoenKampGleixner2025, author = {Hoen, Alexander and Kamp, Dominik and Gleixner, Ambros}, title = {MIP-DD: Delta Debugging for Mixed-Integer Programming Solvers}, journal = {INFORMS Journal on Computing}, doi = {10.1287/ijoc.2024.0844}, year = {2025}, language = {en} } @inproceedings{GonnermannMuellerLeinsGronauetal.2024, author = {Gonnermann-M{\"u}ller, Jana and Leins, Nicolas and Gronau, Norbert and Kosch, Thomas}, title = {Value by design: Reducing Cognitive Load by Using Visual Guidance in Augmented RealityAn Eye-Tracking Study}, booktitle = {Proceedings of the International Conference on Information Systems}, year = {2024}, language = {en} } @inproceedings{GonnermannMuellerBrandenburgerVladovaetal.2023, author = {Gonnermann-M{\"u}ller, Jana and Brandenburger, Bonny and Vladova, Gergana and Gronau, Norbert}, title = {To What Extent Can Individualisation in Terms of Different Types of Mode Improve Learning Outcomes and Learner Satisfaction? A Pre-study}, booktitle = {Proceedings of the Hawaii International Conference on System Sciences}, year = {2023}, language = {en} } @article{HendrychTroppensBesanconetal.2025, author = {Hendrych, Deborah and Troppens, Hannah and Besan{\c{c}}on, Mathieu and Pokutta, Sebastian}, title = {Convex mixed-integer optimization with Frank-Wolfe methods}, volume = {17}, journal = {Mathematical Programming Computation}, doi = {10.1007/s12532-025-00288-w}, pages = {731 -- 757}, year = {2025}, language = {en} } @inproceedings{KumanoKeraYamasaki2024, author = {Kumano, Soichiro and Kera, Hiroshi and Yamasaki, Toshihiko}, title = {Wide Two-Layer Networks can Learn from Adversarial Perturbations}, booktitle = {Proceedings of the Conference on Neural Information Processing Systems}, year = {2024}, language = {en} } @inproceedings{FukudaKeraKawamoto2025, author = {Fukuda, Takuma and Kera, Hiroshi and Kawamoto, Kazuhiko}, title = {Adapter Merging with Centroid Prototype Mapping for Scalable Class-Incremental Learning}, booktitle = {2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, doi = {10.1109/CVPR52734.2025.00460}, pages = {4884 -- 4893}, year = {2025}, language = {en} } @inproceedings{KeraIshiharaKambeetal.2024, author = {Kera, Hiroshi and Ishihara, Yuki and Kambe, Yuta and Vaccon, Tristan and Yokoyama, Kazuhiro}, title = {Learning to Compute Gr\"obner Bases}, booktitle = {Proceedings of the Conference on Neural Information Processing Systems}, year = {2024}, language = {en} } @misc{EbertSchlechteSchwartz2025, author = {Ebert, Patricia and Schlechte, Thomas and Schwartz, Stephan}, title = {Scheduling for German Road Inspectors}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-101999}, year = {2025}, abstract = {For the yearly over 500,000 vehicle inspections of the German Federal Logistics and Mobility Office (BALM), crew rosters must be scheduled to efficiently achieve Germany's road inspection control targets. For that, we present a model to solve the respective duty scheduling and crew rostering problem in order to obtain duty rosters that comply with numerous legal regulations while maximizing the 'control success' to achieve the control targets. We formulate the Template Assignment Problem, which can be modelled as a large scale mixed-integer linear program. Here, feasible combinations of control topics are assigned to the duties using a hypergraph approach. The model is used in production by BALM, and we prove its effectiveness on a number of real-world instances.}, language = {en} } @misc{BetzBinkowskiFischbachetal.2025, author = {Betz, Fridtjof and Binkowski, Felix and Fischbach, Jan David and Feldman, Nick and Zschiedrich, Lin and Rockstuhl, Carsten and Koenderink, A. Femius and Burger, Sven}, title = {Uncovering Hidden Resonances in Non-Hermitian Systems with Scattering Thresholds (Laser Photonics Rev. 19(21)/2025)}, volume = {19}, journal = {Laser Photonics Rev.}, number = {21}, doi = {10.1002/lpor.70534}, pages = {e70534}, year = {2025}, language = {en} } @inproceedings{ManogueSchangKuşetal.2025, author = {Manogue, Kevin and Schang, Tomasz and Ku{\c{s}}, Dilara and M{\"u}ller, Jonas and Zachow, Stefan and Sengupta, Agniva}, title = {Generalizing Shape-from-Template to Topological Changes}, booktitle = {Smart Tools and Applications in Graphics - Eurographics Italian Chapter Conference}, publisher = {The Eurographics Association}, isbn = {978-3-03868-296-7}, arxiv = {http://arxiv.org/abs/2511.03459}, doi = {10.2312/stag.20251322}, year = {2025}, abstract = {Reconstructing the surfaces of deformable objects from correspondences between a 3D template and a 2D image is well studied under Shape-from-Template (SfT) methods; however, existing approaches break down when topological changes accompany the deformation. We propose a principled extension of SfT that enables reconstruction in the presence of such changes. Our approach is initialized with a classical SfT solution and iteratively adapts the template by partitioning its spatial domain so as to minimize an energy functional that jointly encodes physical plausibility and reprojection consistency. We demonstrate that the method robustly captures a wide range of practically relevant topological events including tears and cuts on bounded 2D surfaces, thereby establishing the first general framework for topological-change-aware SfT. Experiments on both synthetic and real data confirm that our approach consistently outperforms baseline methods.}, language = {en} } @misc{SekulicSchaibleMuelleretal.2025, author = {Sekulic, Ivan and Schaible, Jonas and M{\"u}ller, Gabriel and Plock, Matthias and Burger, Sven and Martinez-Lahuerta, Victor J. and Gaaloul, Naceur and Schneider, Philipp-Immanuel}, title = {Data publication for Physics-informed Bayesian optimization of expensive-to-evaluate black-box functions}, journal = {Zenodo}, doi = {10.5281/zenodo.16751507}, year = {2025}, language = {en} } @phdthesis{Plock2025, author = {Plock, Matthias}, title = {On Methods for Bayesian Optimization of Least Squares Problems and Optimization of Nanophotonic Devices}, doi = {10.17169/refubium-48179}, year = {2025}, language = {en} } @inproceedings{ZschiedrichBetzBinkowskietal.2025, author = {Zschiedrich, Lin and Betz, Fridtjof and Binkowski, Felix and Kuen, Lilli and Hammerschmidt, Martin and Burger, Sven}, title = {Efficient Photonic Component Analysis via AAA Rational Approximation}, booktitle = {2025 International Conference on Numerical Simulation of Optoelectronic Devices (NUSOD)}, doi = {10.1109/NUSOD64393.2025.11199710}, pages = {115 -- 116}, year = {2025}, language = {en} } @misc{ZakiyevaPetkovic2025, author = {Zakiyeva, Nazgul and Petkovic, Milena}, title = {Large-scale functional network time series model solved with mathematical programming approach}, journal = {Econometrics and Statistics}, doi = {10.1016/j.ecosta.2025.10.001}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-101936}, year = {2025}, abstract = {A functional network autoregressive model is proposed for studying large-scale network time series observed at high temporal resolution. The model incorporates high-dimensional curves to capture both serial and cross-sectional dependence in large-scale network functional time series. Estimation of the model is approached using a Mixed Integer Optimization method. Simulation studies confirm the consistency of parameter and adjacency matrix estimation. The method is applied to data from a real-life natural gas supply network. Compared to alternative prediction models, the proposed model delivers more accurate day-ahead hourly out-of-sample forecasts of the gas inflows and outflows at most gas nodes.}, language = {en} } @article{LiuZhangLi2025, author = {Liu, Zichen and Zhang, Wei and Li, Tiejun}, title = {Improving the Euclidean Diffusion Generation of Manifold Data by Mitigating Score Function Singularity}, journal = {NeurIPS 2025}, arxiv = {http://arxiv.org/abs/2505.09922}, year = {2025}, abstract = {Euclidean diffusion models have achieved remarkable success in generative modeling across diverse domains, and they have been extended to manifold case in recent advances. Instead of explicitly utilizing the structure of special manifolds as studied in previous works, we investigate direct sampling of the Euclidean diffusion models for general manifold-constrained data in this paper. We reveal the multiscale singularity of the score function in the embedded space of manifold, which hinders the accuracy of diffusion-generated samples. We then present an elaborate theoretical analysis of the singularity structure of the score function by separating it along the tangential and normal directions of the manifold. To mitigate the singularity and improve the sampling accuracy, we propose two novel methods: (1) Niso-DM, which introduces non-isotropic noise along the normal direction to reduce scale discrepancies, and (2) Tango-DM, which trains only the tangential component of the score function using a tangential-only loss function. Numerical experiments demonstrate that our methods achieve superior performance on distributions over various manifolds with complex geometries.}, language = {en} } @misc{ShinanoVigerske2025, author = {Shinano, Yuji and Vigerske, Stefan}, title = {Smoothie: Mixing the strongest MIP solvers to solve hard MIP instances on supercomputers - Phase I development}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-101906}, year = {2025}, abstract = {Mixed-Integer Linear Programming (MIP) is applicable to such a wide range of real-world decision problems that the competition for the best code to solve such problems has lead to tremendous progress over the last decades. While current solvers can solve some of the problems that seemed completely out-of-reach just 10 years ago, there are always relevant MIP problems that currently cannot be solved. With the Smoothie solver we intend to solve extremely hard MIP problems by building on the many years that went into the development of several state-of-the-art MIP solvers and by utilizing some of the largest computing resources available. The high-level task parallelization framework UG (Ubiquity Generator) is used and extended by Smoothie to build a solver that uses large-scale parallelization to distribute the solution of a single MIP on a shared- or distributed-memory computing infrastructure, thereby employing several established MIP solvers simultaneously. For the first development phase, which is the topic of this report, both FICO Xpress and Gurobi are used in concurrent mode on a single machine, while information on incumbent solutions and explored branch-and-bound subtrees is exchanged. A dynamic restarting mechanism ensures that solver configurations are selected that promise most suitable for the MIP to be solved. We report on initial findings using this early version of Smoothie on unsolved problems from MIPLIB 2017.}, language = {en} } @article{ZakiyevaPetkovic2025, author = {Zakiyeva, Nazgul and Petkovic, Milena}, title = {Large-scale functional network time series model solved with mathematical programming approach}, journal = {Econometrics and Statistics}, publisher = {Elsevier BV}, issn = {2452-3062}, doi = {10.1016/j.ecosta.2025.10.001}, year = {2025}, language = {en} } @inproceedings{BortolettoLindner2025, author = {Bortoletto, Enrico and Lindner, Niels}, title = {Scaling and Rounding Periodic Event Scheduling Instances to Different Period Times}, booktitle = {Operations Research Proceedings 2023}, editor = {Voigt, Guido and Fliedner, Malte and Haase, Knut and Br{\"u}ggemann, Wolfgang and Hoberg, Kai and Meissner, J{\"o}rn}, doi = {10.1007/978-3-031-58405-3_51}, pages = {397 -- 402}, year = {2025}, abstract = {The Periodic Event Scheduling Problem (PESP) is a notoriously hard combinatorial optimization problem, essential for the design of periodic timetables in public transportation. The coefficients of the integer variables in the standard mixed integer linear programming formulations of PESP are the period time, e.g., 60 for a horizon of one hour with a resolution of one minute. In many application scenarios, lines with different frequencies have to be scheduled, leading to period times with many divisors. It then seems natural to consider derived instances, where the period time is a divisor of the original one, thereby smaller, and bounds are scaled and rounded accordingly. To this end, we identify two rounding schemes: wide and tight. We then discuss the approximation performance of both strategies, in theory and practice.}, language = {en} } @inproceedings{LindnerLiebchen2025, author = {Lindner, Niels and Liebchen, Christian}, title = {Incremental Heuristics for Periodic Timetabling}, booktitle = {Operations Research Proceedings 2023}, editor = {Voigt, Guido and Fliedner, Malte and Haase, Knut and Br{\"u}ggemann, Wolfgang and Hoberg, Kai and Meissner, J{\"o}rn}, publisher = {Springer Nature Switzerland}, address = {Cham}, doi = {10.1007/978-3-031-58405-3_59}, pages = {461 -- 467}, year = {2025}, abstract = {We present incremental heuristics for the Periodic Event Scheduling Problem (PESP), the standard mathematical tool to optimize periodic timetables in public transport. The core of our method is to solve successively larger subinstances making use of previously found solutions. Introducing the technical notion of free stratifications, we formulate a general scheme for incremental heuristics for PESP. More practically, we use line and station information to create heuristics that add lines or stations one by one, and we evaluate these heuristics on instances of the benchmarking library PESPlib. This approach is indeed viable, and leads to new incumbent solutions for six PESPlib instances.}, language = {en} } @article{KrishnadasMoshiQuintanaetal.2025, author = {Krishnadas, Anirudh and Moshi, Maryam and Quintana, Ramon Alain Miranda and Fournier, Rene}, title = {Geometric Features and a Neural Network Classifier for Detecting Melting-Like Transitions in Clusters.}, journal = {AIP Publications - The Journal of Chemical Physics}, year = {2025}, abstract = {Melting-like transitions in clusters are normally identified by a peak in the heat capacity curve C(T ) at T = Tc. Computing C(T ) requires costly simulations with millions of steps. We discuss four easily calculated functions of temperature that help detect and characterize melting-like transitions. The first, f1 (or WU ), is the width of the potential energy distribution which shows an abrupt increase near Tc. The other three are statistics of the ordered set of N(N - 1)/2 interatomic distances rij: (i) f2 is a measure of dissimilarity to the lowest energy configuration, or global minimum; (ii) f3 is the effective number of rij's found in a small interval centered around (r1 + r2)/2 where r1, r2 are the positions of the first two peaks in the pair distribution function; and (iii) f4 is a measure of non-uniformity in the distribution of the ri j's. Numerical tests with empirical potentials that model three types of bonding (van der Waals, covalent, and metallic) show that f1, f2, f3, and f4 produce estimates for the middle of the melting region in general agreement with Tc. An Artificial Neural Network (ANN) classifier that takes, as inputs, f2, f3, and many variants of f4, is used to calculate the solid fraction FS(T) and find the solid-liquid coexistence region between freezing and melting temperatures, [Tf , Tm]. Inflection points in f3(T ) and FS(T ) are very sensitive indicators of phase transitions. Estimates of Tc obtained from them converge one to three orders of magnitude faster, in simulation time, than those obtained with C(T ).}, language = {en} } @article{KrishnadasCharronFournier2025, author = {Krishnadas, Anirudh and Charron, Nicolas and Fournier, Rene}, title = {Melting Transitions in Small Aluminum Clusters Simulated with Energies Approaching DFT Accuracy.}, journal = {ACS Publications- Journal of Chemical Theory and Computation}, year = {2025}, abstract = {We describe a computational framework for modelling melting-like transitions in atomic clusters that combines first-principles energy calculations, global optimization, and machine-learned interatomic potentials. A diverse set of configurations is generated by global optimization, and energies are calculated by Density Functional Theory. The energies are fitted to an accuracy of 10 meV/atom or better with an Allegro E(3)-equivariant neural network potential. The model allows efficient parallel tempering Monte Carlo simulations with near DFT-level accuracy. This methodology was validated by simulating Na_20 and comparing it to earlier experimental and computational results. We used it to study melting-like transitions in Al_n+ clusters (n=9 to 16), and Al_n and Al_n^- (n=12, 13,14). The simulated heat capacity of these clusters, in particular Al_16+, are in qualitative agreement with experiments. The melting point of Al_n+ clusters with n=11-16 are well above the bulk melting point (934 K). The closed-shell Al_13- species has an exceptionally high melting point, close to 2100 K.}, language = {en} } @article{KrishnadasSinhaKirchneretal.2024, author = {Krishnadas, Anirudh and Sinha, Nidhi and Kirchner, Tom and Antony, Bobby}, title = {Calculation of electron-impact ionization of various benzene derivatives}, volume = {99}, journal = {IOP Publications- Physica Scripta}, number = {9}, doi = {10.1088/1402-4896/ad640a}, pages = {095403}, year = {2024}, abstract = {Calculations of the electron-impact ionization cross-section of pyrene, anthracene, benzoyl chloride, benzophenone, and phthalonitrile are reported over a wide energy range. A comparison of theoretical models, viz. spherical complex optical potential (SCOP), pixel counting method (PCM), and the binary encounter Bethe (BEB) model is carried out. SCOP calculations provide the inelastic cross-section, and the ionization cross-section is extracted from it. This result is modified with PCM, a model previously applied to ion collisions which takes geometric screening corrections into account. The BEB model is used as an independent approach to calculate the ionization cross-section. It is demonstrated that all model results are in reasonable agreement with each other. Comparison is also made with other theoretical data where available.}, language = {en} } @inproceedings{LoebelLindner2025, author = {L{\"o}bel, Fabian and Lindner, Niels}, title = {A Geometric Approach to Integrated Periodic Timetabling and Passenger Routing}, volume = {137}, booktitle = {25th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2025)}, editor = {Sauer, Jonas and Schmidt, Marie}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, isbn = {978-3-95977-404-8}, issn = {2190-6807}, doi = {10.4230/OASIcs.ATMOS.2025.2}, url = {http://nbn-resolving.de/urn:nbn:de:0030-drops-247580}, pages = {2:1 -- 2:19}, year = {2025}, abstract = {We offer a geometric perspective on the problem of integrated periodic timetabling and passenger routing in public transport. Inside the space of periodic tensions, we single out those regions, where the same set of paths provides shortest passenger routes. This results in a polyhedral subdivision, which we combine with the known decomposition by polytropes. On each maximal region of the common refinement, the integrated problem is solvable in polynomial time. We transform these insights into a new geometry-driven primal heuristic, integrated tropical neighborhood search (ITNS). Computationally, we compare implementations of ITNS and the integrated (restricted) modulo network simplex algorithm on the TimPassLib benchmark set, and contribute better solutions in terms of total travel time for all but one of the twenty-five instances for which a proven optimal solution is not yet known.}, language = {en} } @inproceedings{GhannamGleixner2025, author = {Ghannam, Mohammed and Gleixner, Ambros}, title = {Hybrid Genetic Search for Dynamic Vehicle Routing with Time Windows}, booktitle = {Operations Research Proceedings 2023. OR 2023}, doi = {10.1007/978-3-031-58405-3_35}, year = {2025}, language = {en} } @article{OkaforntaFarhadifarFabigetal.2025, author = {Okafornta, Chukwuebuka William and Farhadifar, Reza and Fabig, Gunar and Wu, Hai-Yin and K{\"o}ckert, Maria and Vogel, Martin and Baum, Daniel and Haase, Robert and Shelley, Michael J. and Needleman, Daniel J. and M{\"u}ller-Reichert, Thomas}, title = {Cell size reduction scales spindle elongation but not chromosome segregation in C. elegans}, journal = {bioRxiv}, doi = {10.1101/2025.10.13.681585}, year = {2025}, abstract = {How embryos adapt their internal cellular machinery to reductions in cell size during development remains a fundamental question in cell biology. Here, we use high-resolution lattice light-sheet fluorescence microscopy and automated image analysis to quantify lineage-resolved mitotic spindle and chromosome segregation dynamics from the 2- to 64-cell stages in Caenorhabditis elegans embryos. While spindle length scales with cell size across both wild-type and size-perturbed embryos, chromosome segregation dynamics remain largely invariant, suggesting that distinct mechanisms govern these mitotic processes. Combining femtosecond laser ablation with large-scale electron tomography, we find that central spindle microtubules mediate chromosome segregation dynamics and remain uncoupled from cell size across all stages of early development. In contrast, spindle elongation is driven by cortically anchored motor proteins and astral microtubules, rendering it sensitive to cell size. Incorporating these experimental results into an extended stoichiometric model for both the spindle and chromosomes, we find that allowing only cell size and microtubule catastrophe rates to vary reproduces elongation dynamics across development. The same model also accounts for centrosome separation and pronuclear positioning in the one-cell C. elegans embryo, spindle-length scaling across nematode species spanning ~100 million years of divergence, and spindle rotation in human cells. Thus, a unified stoichiometric framework provides a predictive, mechanistic account of spindle and nuclear dynamics across scales and species.}, language = {en} } @article{RiedmuellerLindner2025, author = {Riedm{\"u}ller, Stephanie and Lindner, Niels}, title = {Column Generation for Periodic Timetabling}, arxiv = {http://arxiv.org/abs/2510.12466}, year = {2025}, abstract = {Periodic timetabling for public transportation networks is typically modelled as a Periodic Event Scheduling Problem (PESP). Solving instances of the benchmark library PESPlib to optimality continues to pose a challenge. As a further approach towards this goal, we remodel the problem by a time discretization of the underlying graph and consider arc-based as well as path-based integer programming formulations. For the path-based case, we use cycles on the graph expansion of the operational lines as variables and, therefore, include more of the problem inherent structure into the model. A consequence is the validity of several known inequalities and a lower bound on the LP-relaxation, that is the best known to date. As an extension we integrate passenger routing into the new model. The proposed models have an advantage in the linear programming relaxation, on the one hand, but have an increased problem size, on the other hand. We define the corresponding pricing problems for the use of column generation to handle the size. Both models are practically tested on different problem instances.}, language = {en} } @article{GonnermannMuellerHaaseFackeldeyetal.2025, author = {Gonnermann-M{\"u}ller, Jana and Haase, Jennifer and Fackeldey, Konstantin and Pokutta, Sebastian}, title = {FACET: Teacher-Centred LLM-Based Multi-Agent Systems-Towards Personalized Educational Worksheets}, arxiv = {http://arxiv.org/abs/2508.11401}, year = {2025}, abstract = {The increasing heterogeneity of student populations poses significant challenges for teachers, particularly in mathematics education, where cognitive, motivational, and emotional differences strongly influence learning outcomes. While AI-driven personalization tools have emerged, most remain performance-focused, offering limited support for teachers and neglecting broader pedagogical needs. This paper presents the FACET framework, a teacher-facing, large language model (LLM)-based multi-agent system designed to generate individualized classroom materials that integrate both cognitive and motivational dimensions of learner profiles. The framework comprises three specialized agents: (1) learner agents that simulate diverse profiles incorporating topic proficiency and intrinsic motivation, (2) a teacher agent that adapts instructional content according to didactical principles, and (3) an evaluator agent that provides automated quality assurance. We tested the system using authentic grade 8 mathematics curriculum content and evaluated its feasibility through a) automated agent-based assessment of output quality and b) exploratory feedback from K-12 in-service teachers. Results from ten internal evaluations highlighted high stability and alignment between generated materials and learner profiles, and teacher feedback particularly highlighted structure and suitability of tasks. The findings demonstrate the potential of multi-agent LLM architectures to provide scalable, context-aware personalization in heterogeneous classroom settings, and outline directions for extending the framework to richer learner profiles and real-world classroom trials.}, language = {en} } @misc{OPUS4-10176, title = {Mathematical Optimization for Machine Learning}, editor = {Fackeldey, Konstantin and Kannan, Aswin and Pokutta, Sebastian and Sharma, Kartikey and Walter, Daniel and Walter, Andrea and Weiser, Martin}, publisher = {De Gruyter}, isbn = {9783111376776}, doi = {10.1515/9783111376776}, year = {2025}, abstract = {Mathematical optimization and machine learning are closely related. This proceedings volume of the Thematic Einstein Semester 2023 of the Berlin Mathematics Research Center MATH+ collects recent progress on their interplay in topics such as discrete optimization, nonlinear programming, optimal control, first-order methods, multilevel optimization, machine learning in optimization, physics-informed learning, and fairness in machine learning.}, language = {en} } @article{AndresArconesWeiserKoutsourelakisetal.2026, author = {Andr{\´e}s Arcones, Daniel and Weiser, Martin and Koutsourelakis, Phaedon-Stelios and Unger, J{\"o}rg F.}, title = {Embedded Model Form Uncertainty Quantification with Measurement Noise for Bayesian Model Calibration}, volume = {7}, journal = {Data-Centric Engineering}, arxiv = {http://arxiv.org/abs/2410.12037}, doi = {10.1017/dce.2025.10035}, year = {2026}, abstract = {A key factor in ensuring the accuracy of computer simulations that model physical systems is the proper calibration of their parameters based on real-world observations or experimental data. Inevitably, uncertainties arise, and Bayesian methods provide a robust framework for quantifying and propagating these uncertainties to model predictions. Nevertheless, Bayesian methods paired with inexact models usually produce predictions unable to represent the observed datapoints. Additionally, the quantified uncertainties of these overconfident models cannot be propagated to other Quantities of Interest (QoIs) reliably. A promising solution involves embedding a model inadequacy term in the inference parameters, allowing the quantified model form uncertainty to influence non-observed QoIs. This paper introduces a more interpretable framework for embedding the model inadequacy compared to existing methods. To overcome the limitations of current approaches, we adapt the existing likelihood models to properly account for noise in the measurements and propose two new formulations designed to address their shortcomings. Moreover, we evaluate the performance of this inadequacy-embedding approach in the presence of discrepancies between measurements and model predictions, including noise and outliers. Particular attention is given to how the uncertainty associated with the model inadequacy term propagates to the QoIs, enabling a more comprehensive statistical analysis of prediction's reliability. Finally, the proposed approach is applied to estimate the uncertainty in the predicted heat flux from a transient thermal simulation using temperature bservations.}, language = {en} } @article{AgarwalGreveReinefeldetal.2025, author = {Agarwal, A. and Greve, Nico and Reinefeld, Alexander and Schintke, Florian and et al.,}, title = {Performance of the prototype Silicon Tracking System of the CBM experiment tested with heavy-ion beams at SIS18}, volume = {1082}, journal = {Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment}, publisher = {Elsevier BV}, issn = {0168-9002}, arxiv = {http://arxiv.org/abs/2505.20517}, doi = {10.1016/j.nima.2025.171059}, pages = {171059}, year = {2025}, language = {en} } @article{XieGruberCrampenetal.2025, author = {Xie, Kunpeng and Gruber, Lennart Johannes and Crampen, Martin and Li, Yao and Ferreira, Andr{\´e} and Tappeiner, Elias and Gillot, Maxime and Schepers, Jan and Xu, Jiangchang and Pankert, Tobias and Beyer, Michel and Shahamiri, Negar and ten Brink, Reinier and Dot, Gauthier and Weschke, Charlotte and van Nistelrooij, Niels and Verhelst, Pieter-Jan and Guo, Yan and Xu, Zhibin and Bienzeisler, Jonas and Rashad, Ashkan and Fl{\"u}gge, Tabea and Cotton, Ross and Vinayahalingam, Shankeeth and Ilesan, Robert and Raith, Stefan and Madsen, Dennis and Seibold, Constantin and Xi, Tong and Berg{\´e}, Stefaan and Nebelung, Sven and Kodym, Oldřich and Sundqvist, Osku and Thieringer, Florian and Lamecker, Hans and Coppens, Antoine and Potrusil, Thomas and Kraeima, Joep and Witjes, Max and Wu, Guomin and Chen, Xiaojun and Lambrechts, Adriaan and Cevidanes, Lucia H Soares and Zachow, Stefan and Hermans, Alexander and Truhn, Daniel and Alves, Victor and Egger, Jan and R{\"o}hrig, Rainer and H{\"o}lzle, Frank and Puladi, Behrus}, title = {Beyond Benchmarks: Towards Robust Artificial Intelligence Bone Segmentation in Socio-Technical Systems}, volume = {299}, journal = {Expert Systems With Applications}, number = {Part D}, doi = {10.1016/j.eswa.2025.130031}, year = {2025}, abstract = {Despite the advances in automated medical image segmentation, AI models still underperform in various clinical settings, challenging real-world integration. In this multicenter evaluation, we analyzed 20 state-of-the-art mandibular segmentation models across 19,218 segmentations of 1,000 clinically resampled CT/CBCT scans. We show that segmentation accuracy varies by up to 25\% depending on socio-technical factors such as voxel size, bone orientation, and patient conditions such as osteosynthesis or pathology. Higher sharpness, isotropic smaller voxels, and neutral orientation significantly improved results, while metallic osteosynthesis and anatomical complexity led to significant degradation. Our findings challenge the common view of AI models as "plug-and-play" tools and suggest evidence-based optimization recommendations for both clinicians and developers. This will in turn boost the integration of AI segmentation tools in routine healthcare.}, language = {en} } @phdthesis{Amiranashvili2025, author = {Amiranashvili, Tamaz}, title = {Universal and Expressive Statistical Shape Models for Anatomical Structures}, school = {Technische Universit{\"a}t M{\"u}nchen}, pages = {86}, year = {2025}, abstract = {Form and function of anatomical structures are intimately linked. Pathological changes in form can be associated with the loss of function. For example, diseases often cause characteristic shape changes, making shape a sensitive structural biomarker for medical diagnosis. If the link between form and function is causal, correcting a pathological shape can even restore the healthy function of an organ. Accurate shape reconstruction is then crucial for effective, patient-specific treatment planning. This demonstrates the importance of shape in clinical interventions and its potential to improve overall patient outcomes. Statistical shape models are computational methods that capture shape variations in a given population and enable precise shape analysis and generation. We focus on two key properties of a good statistical shape model. First, it should be easy to construct, and second, it should accurately represent the underlying shape distribution. Established existing approaches can only be constructed from surfaces with pre-defined dense correspondence. Such correspondence is tedious to obtain, can introduce undesired biases, and prevents training on partial or sparse observations. While correspondence-free methods exist, they struggle to accurately capture shape distributions with intricate details and large variations. In this thesis, we develop shape models that simplify training and improve accuracy over state-of-the-art. To achieve these goals, we build on approximately diffeomorphic neural deformations and implicit neural representations. First, our proposed methods are trainable on correspondence-free surfaces and even partial segmentations with large slice distances. This makes them universal since they can be trained on heterogeneous data, enabling scalability to large datasets and avoiding potential biases of pre-defined correspondence. Second, our methods are highly expressive, accurately capturing intricate shape details in complex distributions. We evaluate effectiveness of our models on multiple anatomical structures, outperforming established baselines in both generative and discriminative settings.}, language = {en} } @misc{Oezmen2022, type = {Master Thesis}, author = {{\"O}zmen, Mahmut}, title = {Medical Image registration with B-Spline Transformation}, pages = {64}, year = {2022}, abstract = {Medical image registration is an important task in various applications such as temporal analysis of medical images from a single modality (where structural or anatomical changes over time are studied), multi-modal image fusion (in which data acquired from different imaging devices or protocols is fused to help with diagnosis and treatment planning), or atlas matching (where uses normal anatomical variability). Establishing functional and/or spatial anatomical correspondences between different image acquisitions is the goal of image registration. As rigid alignment might be insufficient to describe variations of images in certain applications where deformations play a role, we should rely on non-rigid image registration. Non-rigid registration methods are capable of aligning images where correspondence cannot be achieved without localized deformations and can therefore better accommodate anatomical, physiological, and pathological variability between patients. Elastix image registration software is employed in this thesis to conduct our experiments. In this thesis, we use interpolation-based B-spline transformation models that parameterize a Free-Form Deformation Field. B-splines interpolate the dense deformation field from a given set of control points. B-spline transformation model assumes the smoothness and continuity of the deformation field on the image. However, when aligning two images that contain sliding contact, B-spline transformation leads to an inaccurate registration result, and the deformation field is not always smooth or the deformation field is always discontinuous, but not necessarily everywhere. When the knee is bent, the sliding contact occurs at the knee cartilage and around the capsular tissues. Different types of discontinuities in the overall deformation field may occur when sliding contact occurs. Imposing smoothness and continuity in the registration will generate artifacts in the consequent deformations, as well as any quantities derived from it. To handle the artifacts in the resulting deformations, one can use a regularizer or implement the sliding motion in the transformation model. Hence, in this thesis, we compare the B-spline registration, B-spline with Transform Rigidity Penalty, B-spline with Distance Rigidity Penalty, and the sliding motion with B-splines. B-spline with Transform Rigidity Penalty (TRP) and B-spline with Distance Rigidity Penalty (DPRP) models use a regularizer to handle the sliding motion. However, the sliding Motion with B-splines model handles sliding motion in the transformation model itself. The chosen registration parameters and registration algorithm were assessed first using three synthetic datasets. In a second validation, Knee MRI images that belong to two different patient datasets are registered on a temporal sequence of each patient. Registration accuracy was assessed based on the corresponding segmented bones and neighboring soft tissue. Compared to B-spline approach, the B-spline with TRP, B-spline with DPRP, and the sliding motion with B-splines gave deformation fields that represented more plausible image correspondences, while giving rise to comparable registration accuracy. In one dataset, the B-spline with TRP and B-spline with DPRP models reflected the deformation better than other approaches. However, sliding motion with B-splines model outperformed all other approaches in the other dataset.}, language = {en} } @misc{Kasravi2024, type = {Master Thesis}, author = {Kasravi, Javad}, title = {Completion of Missing Parts in Medical Images Using Generative Adversarial Networks and Transformers}, pages = {70}, year = {2024}, abstract = {Image inpainting (image completion) is a technique to remove undesirable elements or fill missing (repair damaged) sections in an image [1]. In medical images, inpainting can be applied for various applications. Issues like image artifacts (e.g., metal artifacts in CT and MRI) can introduce alterations to medical images. In simpler terms, these artifacts may introduce unwanted elements or anomalies into the medical images. These unwanted elements can be replaced with appropriate intensity in the images. In the context of defect reconstruction, which involves repairing skull defects, medical images are taken. To design an implant for a defective skull, image inpainting can be applied to an image containing the defective skull. This process generates an image with skull tissue, which can then be utilized for implant design. Additionally, in situations involving a restricted field of view, such as when only accessing the lower part of the full-body MRI, predicting the missing information (e.g., the upper part of the full-body MRI) can be beneficial for subsequent tasks, such as extracting bone structures for 3D shape modeling studies. Another application of inpainting is observed during actual stereo-fluoroscopic X-ray measurements. In these measurements, the calibration grid, which is beneficial for correcting distortions, introduces unwanted black dots into the image content. These black dots need to be removed from the image and replaced with the appropriate intensity. This thesis extends an existing architecture named Mask-aware Transformer (MAT) to fill in missing information in medical scans. The proposed method utilizes Generative Adversarial Networks and a Mask-aware Swin Transformer. Various adjustments, including changes in data type, model architecture, and adaptation for multinode training, have been implemented to address missing information in three different datasets. In one of our datasets, where black dots disrupt the image content, we applied our method to fill in the missing information. The results indicate that our approach outperforms other model-driven methods. In the second dataset, we employed the German National Cohort full-body MRI dataset to train a network for predicting the upper part of the full-body MRI. The outcomes indicate that the generated 2D slices exhibit realism and perform well in both pixel-wise and perceptual metrics. However, when these 2D slices are stacked into a 3D volume, inconsistencies between different slices become apparent. Furthermore, when we compare our 2D-aware image inpainting method to 3D inpainting algorithms used in the Brain Tumor Segmentation 2023 challenge, the results confirm the findings of the earlier experiment. The 2D slices produced are realistic, but there is inconsistency between them. In summary, theMAT demonstrates its ability to capture global dependencies by utilizing an adapted Swin Transformer for X-ray images, inherently 2D images. The results for 2D slices from a 3D MRI volume are also reasonable because the network is trained specifically on 2D slices. However, due to the lack of awareness regarding this architecture in the third dimension, inconsistencies between slices are observed.}, language = {en} } @misc{Menguellueoglu2022, type = {Master Thesis}, author = {Meng{\"u}ll{\"u}oglu, Eceg{\"u}l}, title = {Analysis of the NORA Anaphylaxis Database: Towards Identifying Severity Factors using Machine Learning}, pages = {47}, year = {2022}, abstract = {Anaphylaxis is a severe allergic reaction, which occurs instantaneously with potential life-threatening symptoms by affecting different organ systems. The reaction could be triggered by an exposure to various types of allergens including foods, drugs, insects, venom and others. The European Anaphylaxis Registry (NORA) is a large database gathered to collect information on anaphylaxis cases through the allergy centers in European and other countries. This questionnaire-based survey data was designed in a way to provide information on patients' demographic characteristics, eliciting allergens, symptoms, reaction severity, emergency treatment and long-term management of the disease and aims to improve the knowledge on reactions and provide treatment methods to affected patients. Unfortunately, the data is partly incomplete. However, incomplete data hinders some algorithms to work properly and may lead to misleading analysis results. Another issue regarding the dataset is, it contains a large number of variables, which introduces complex linear or/and non-linear relationships to the data and makes it difficult to reveal those relationships, which makes analyzing and driving conclusions from the data a challenging task. The problems mentioned above, leads us to the questions asked in this thesis. The fact that the data is incomplete raises the main question, which is whether and how it is possible to impute the missing data and how this affects subsequent steps, such as classification. The size and the complexity of the data raises the second question: Are there certain relationships within variables that can be used to predict the severity of the disease? In case there is, are there any potential augmentation factors, also called cofactors in the dataset that may increase the severity of a reaction to an allergen that would normally not occur when the cofactor does not exist? As explained, the goal of this thesis is to find answers to the questions indicated above. For that reason, initially, we searched for a suitable method for data imputation and compared performances of two different tree-based multiple imputation methods on the dataset. After obtaining multiple complete datasets, we tried to predict the severity of anaphylaxis from the dataset to determine hidden risk factors behind anaphylaxis using high power gradient boosting methods. It is concluded that, multiple imputation with chained equations (MICE) based on classification and regression trees can be useful for imputing NORA dataset. However, we could not detect enough associations between study variables and anaphylaxis severity in the data, to predict anaphylaxis severity from the dataset.}, language = {en} } @misc{Lukanek2024, type = {Master Thesis}, author = {Lukanek, Sandra}, title = {3D Reconstruction of the Mandible from Panoramic Dental X-Ray Projections}, pages = {49}, year = {2024}, abstract = {Panoramic radiography is a popular imaging technique in dental medicine. It omprehensively represents the entire jaw, including the mandible, maxilla, and teeth in a compact two-dimensional (2D) image. It offers several advantages over three-dimensional (3D) imaging, such as Cone Beam Computed Tomography (CBCT), including cost-effectiveness and reduced radiation exposure. However, its major drawback lies in its ambiguities in spatial distribution, leading to inaccuracies in linear measurements due to the dependency on the parameters used for generating the image. In this thesis, we propose a methodology for reconstructing a 3D anatomy of the mandible from a given 2D panoramic X-ray image. Our approach involves extracting information from the 2D scan, considering the projection geometry, and aiming to achieve a realistic spatial distribution. The methodology builds upon an existing intensity-based 2D-3D registration algorithm, which is modified to accommodate the unique geometric parameters of panoramic radiography. By employing a virtual X-ray setup, we generate a panoramic X-ray from a Statistical Shape and Intensity Model (SSIM) derived from 25 tetrahedral meshes. The intensity information for each mesh is extracted from CBCT scans representing jaw anatomies. To reconstruct the true mandible, the model is iteratively optimized by comparing the simulated X-ray with the original panoramic X-ray. We evaluate and establish the setup using synthetically generated panoramic X-rays from multiple mandibles obtained from CBCT scans. After analyzing the feasibility of this method, we conclude that 2D-3D registration for panoramic X-rays presents a challenging task, as the ambiguity of the 2D projection involved in panoramic X-ray imaging can result in varied 3D shape representations.}, language = {en} } @article{SatoKochLe2026, author = {Sato, Mako and Koch, Thorsten and Le, Thi Thai}, title = {Influence of frictional drag on Kelvin-Helmholtz instability in viscous fluids}, volume = {38}, journal = {Physics of Fluids}, number = {1}, publisher = {AIP Publishing}, address = {Physics of Fluids}, doi = {10.1063/5.0306177}, year = {2026}, abstract = {The Kelvin-Helmholtz instability arises at the interface between two fluid layers with a tangential velocity discontinuity, significantly impacting the safety of systems in industrial applications. Despite extensive studies, many theoretical analyses neglect viscosity and frictional drag due to the complexity of solving the dispersion equation. However, including these effects is crucial, as viscosity alters the growth rate of the instability, while frictional drag influences energy dissipation and momentum transfer. In this study, these effects are incorporated into both finite and infinite flows. The assumption of a potential flow combined with a dissipation method is employed to derive the dispersion equation, providing a more tractable approach than direct calculation methods. The results indicate that, in the case of infinite flows, the frictional drag suppresses the growth of the instability for long waves (small wavenumber k) but enhances it for short waves (large k). In contrast, the surface tension dominates, while the frictional drag only slightly affects the growth rate in the case of finite flows bounded by solid walls.}, language = {en} } @article{HuTutikaDengetal.2025, author = {Hu, Chenhao and Tutika, Ravi and Deng, Zhifei and Jia, Zian and Chen, Liuni and Chen, Hongshun and Geng, Yang and Xiao, Xianghui and Shevchenko, Pavel D. and Pierre, Christoph and Weaver, James C. and Baum, Daniel and Bartlett, Michael D. and Li, Ling}, title = {Mineralized sclerites in the gorgonian coral Leptogorgia chilensis as a natural jamming system}, volume = {122}, journal = {PNAS}, number = {44}, doi = {10.1073/pnas.2504541122}, year = {2025}, language = {en} } @inproceedings{JaegerMandalRandetal.2025, author = {J{\"a}ger, Klaus and Mandal, Jyotirmoy and Rand, Barry P. and Meggers, Forrest and Becker, Christiane}, title = {Thermal Management of Solar Modules with Infrared-Antireflective Coatings}, volume = {SOLITH}, booktitle = {Advanced Photonics Congress}, doi = {10.1364/SOLITH.2025.SM4E.2}, pages = {SM4E.2}, year = {2025}, language = {en} } @article{ZittelPetkovicEinck2025, author = {Zittel, Janina and Petkovic, Milena and Einck, Mathias}, title = {Forecasting Hourly Gas Flows}, volume = {79}, journal = {Foresight - The International Journal of Applied Forecasting}, pages = {40 -- 44}, year = {2025}, language = {en} } @article{KiesslingLeyfferVanaret2025, author = {Kießling, David and Leyffer, Sven and Vanaret, Charlie}, title = {A Unified Funnel Restoration SQP Algorithm}, journal = {Mathematical Programming B}, doi = {10.1007/s10107-025-02284-3}, year = {2025}, abstract = {We consider nonlinearly constrained optimization problems and discuss a generic double-loop framework consisting of basic algorithmic ingredients that unifies a broad range of nonlinear optimization solvers. This framework has been implemented in the open-source solver Uno, a Swiss Army knife-like C++ optimization framework that unifies many nonlinearly constrained nonconvex optimization solvers. We illustrate the framework with a sequential quadratic programming (SQP) algorithm that maintains an acceptable upper bound on the constraint violation, called a funnel, that is monotonically decreased to control the feasibility of the iterates. Infeasible quadratic subproblems are handled by a feasibility restoration strategy. Globalization is controlled by a line search or a trust-region method. We prove global convergence of the trust-region funnel SQP method, building on known results from filter methods. We implement the algorithm in Uno, and we provide extensive test results for the trust-region line-search funnel SQP on small CUTEst instances.}, language = {en} } @article{BartoliSengupta2025, author = {Bartoli, Adrien and Sengupta, Agniva}, title = {Camera Pose in SfT and NRSfM under Isometric and Weaker Deformation Models}, volume = {261}, journal = {Computer Vision and Image Understanding}, doi = {10.1016/j.cviu.2025.104488}, year = {2025}, abstract = {Camera pose is a very natural concept in 3D vision in the rigid setting. It is however much more difficult to work with in deformable settings. Consequently, numerous deformable reconstruction methods simply ignore camera pose. We analyse the concept of pose in deformable settings and prove that it is unconstrained with the existing formulations, properly justifying the existing pose-less methods reconstructing structure only. We explain this result intuitively by the impossibility to define an intrinsic coordinate frame to a general deforming object. The proposed analysis uses the isometric deformation model and extends to the weaker models including conformality and equiareality. We propose a novel prior to rescue camera pose estimation in deformable settings, which attributes the deforming object's dominant rigid-body motion to the camera. We show that adding this prior to any existing formulation fully constrains camera pose and leads to elegant two-step solution methods, involving deformable structure reconstruction using a base method in the first step, and absolute orientation or Procrustes analysis in the second step. We derive the proposed approach for the template-based and template-less settings, respectively implemented using Shape-from-Template (SfT) and Non-Rigid Structure-from-Motion (NRSfM) as base methods, and validate them experimentally, showing that the computed pose is qualitatively and quantitatively plausible.}, language = {en} } @misc{DoerffelMikulaSchielickeetal.2025, author = {D{\"o}rffel, Tom and Mikula, Natalia and Schielicke, Lisa and Kiszler, Theresa and Faranda, Davide and Debrulle, B{\´e}reng{\`e}re and Vercauteren, Nikki}, title = {Characterizing inertial and diabatic energy transfers in tropical cyclones: Data}, doi = {10.12752/10135}, year = {2025}, abstract = {The multiscale organization of tropical cyclones (TCs) is investigated by means of three-dimensional data produced by the atmospheric model CM1. We provide a sample dataset in NetCDF format covering the TC evolution from incipient to mature under the influence of externally imposed wind shear. This dataset serves as a testbed for applying energy-tranfer analyses based on the Duchon-Robert index as well as diabatic transfer based on an asymptotic theory on TCs.}, language = {en} } @inproceedings{SchneiderSekulicPlocketal.2025, author = {Schneider, Philipp-Immanuel and Sekulic, Ivan and Plock, Matthias and Hammerschmidt, Martin and Rodt, Sven and Reitzenstein, Stephan and Burger, Sven}, title = {Physics-informed Bayesian optimization of nanophotonic devices}, volume = {IPRSN}, booktitle = {Advanced Photonics Congress}, doi = {10.1364/IPRSN.2025.ITu1A.2}, pages = {ITu1A.2}, year = {2025}, language = {en} } @article{ReussMacdonaldBeckeretal.2025, author = {Reuss, Joana and Macdonald, Jan and Becker, Simon and Schultka, Konrad and Richter, Lorenz and K{\"o}rner, Marco}, title = {Meta-learning For Few-Shot Time Series Crop Type Classification: A Benchmark On The EuroCropsML Dataset}, arxiv = {http://arxiv.org/abs/2504.11022}, year = {2025}, abstract = {Spatial imbalances in crop type data pose significant challenges for accurate classification in remote sensing applications. Algorithms aiming at transferring knowledge from data-rich to data-scarce tasks have thus surged in popularity. However, despite their effectiveness in previous evaluations, their performance in challenging real-world applications is unclear and needs to be evaluated. This study benchmarks transfer learning and several meta-learning algorithms, including (First-Order) Model-Agnostic Meta-Learning ((FO)-MAML), Almost No Inner Loop (ANIL), and Task-Informed Meta-Learning (TIML), on the real-world EuroCropsML time series dataset, which combines farmer-reported crop data with Sentinel-2 satellite observations from Estonia, Latvia, and Portugal. Our findings indicate that MAML-based meta-learning algorithms achieve slightly higher accuracy compared to simpler transfer learning methods when applied to crop type classification tasks in Estonia after pre-training on data from Latvia. However, this improvement comes at the cost of increased computational demands and training time. Moreover, we find that the transfer of knowledge between geographically disparate regions, such as Estonia and Portugal, poses significant challenges to all investigated algorithms. These insights underscore the trade-offs between accuracy and computational resource requirements in selecting machine learning methods for real-world crop type classification tasks and highlight the difficulties of transferring knowledge between different regions of the Earth. To facilitate future research in this domain, we present the first comprehensive benchmark for evaluating transfer and meta-learning methods for crop type classification under real-world conditions. The corresponding code is publicly available at this https URL.}, language = {en} } @inproceedings{ChenRichterBerneretal.2025, author = {Chen, Junhua and Richter, Lorenz and Berner, Julius and Blessing, Denis and Neumann, Gerhard and Anandkumar, Anima}, title = {Sequential Controlled Langevin Diffusions}, booktitle = {13th International Conference on Learning Representations (ICLR 2025)}, arxiv = {http://arxiv.org/abs/2412.07081}, year = {2025}, abstract = {An effective approach for sampling from unnormalized densities is based on the idea of gradually transporting samples from an easy prior to the complicated target distribution. Two popular methods are (1) Sequential Monte Carlo (SMC), where the transport is performed through successive annealed densities via prescribed Markov chains and resampling steps, and (2) recently developed diffusion-based sampling methods, where a learned dynamical transport is used. Despite the common goal, both approaches have different, often complementary, advantages and drawbacks. The resampling steps in SMC allow focusing on promising regions of the space, often leading to robust performance. While the algorithm enjoys asymptotic guarantees, the lack of flexible, learnable transitions can lead to slow convergence. On the other hand, diffusion-based samplers are learned and can potentially better adapt themselves to the target at hand, yet often suffer from training instabilities. In this work, we present a principled framework for combining SMC with diffusion-based samplers by viewing both methods in continuous time and considering measures on path space. This culminates in the new Sequential Controlled Langevin Diffusion (SCLD) sampling method, which is able to utilize the benefits of both methods and reaches improved performance on multiple benchmark problems, in many cases using only 10\% of the training budget of previous diffusion-based samplers.}, language = {en} } @article{BernerRichterSenderaetal.2025, author = {Berner, Julius and Richter, Lorenz and Sendera, Marcin and Rector-Brooks, Jarrid and Malkin, Nikolay}, title = {From discrete-time policies to continuous-time diffusion samplers: Asymptotic equivalences and faster training}, arxiv = {http://arxiv.org/abs/2501.06148}, year = {2025}, abstract = {We study the problem of training neural stochastic differential equations, or diffusion models, to sample from a Boltzmann distribution without access to target samples. Existing methods for training such models enforce time-reversal of the generative and noising processes, using either differentiable simulation or off-policy reinforcement learning (RL). We prove equivalences between families of objectives in the limit of infinitesimal discretization steps, linking entropic RL methods (GFlowNets) with continuous-time objects (partial differential equations and path space measures). We further show that an appropriate choice of coarse time discretization during training allows greatly improved sample efficiency and the use of time-local objectives, achieving competitive performance on standard sampling benchmarks with reduced computational cost.}, language = {en} } @inproceedings{BlessingBernerRichteretal.2025, author = {Blessing, Denis and Berner, Julius and Richter, Lorenz and Neumann, Gerhard}, title = {Underdamped Diffusion Bridges with Applications to Sampling}, booktitle = {13th International Conference on Learning Representations (ICLR 2025)}, arxiv = {http://arxiv.org/abs/2503.01006}, year = {2025}, abstract = {We provide a general framework for learning diffusion bridges that transport prior to target distributions. It includes existing diffusion models for generative modeling, but also underdamped versions with degenerate diffusion matrices, where the noise only acts in certain dimensions. Extending previous findings, our framework allows to rigorously show that score matching in the underdamped case is indeed equivalent to maximizing a lower bound on the likelihood. Motivated by superior convergence properties and compatibility with sophisticated numerical integration schemes of underdamped stochastic processes, we propose \emph{underdamped diffusion bridges}, where a general density evolution is learned rather than prescribed by a fixed noising process. We apply our method to the challenging task of sampling from unnormalized densities without access to samples from the target distribution. Across a diverse range of sampling problems, our approach demonstrates state-of-the-art performance, notably outperforming alternative methods, while requiring significantly fewer discretization steps and no hyperparameter tuning.}, language = {en} } @article{BlessingBernerRichteretal.2025, author = {Blessing, Denis and Berner, Julius and Richter, Lorenz and Domingo-Enrich, Carles and Du, Yuanqi and Vahdat, Arash and Neumann, Gerhard}, title = {Trust Region Constrained Measure Transport in Path Space for Stochastic Optimal Control and Inference}, arxiv = {http://arxiv.org/abs/2508.12511}, year = {2025}, abstract = {Solving stochastic optimal control problems with quadratic control costs can be viewed as approximating a target path space measure, e.g. via gradient-based optimization. In practice, however, this optimization is challenging in particular if the target measure differs substantially from the prior. In this work, we therefore approach the problem by iteratively solving constrained problems incorporating trust regions that aim for approaching the target measure gradually in a systematic way. It turns out that this trust region based strategy can be understood as a geometric annealing from the prior to the target measure, where, however, the incorporated trust regions lead to a principled and educated way of choosing the time steps in the annealing path. We demonstrate in multiple optimal control applications that our novel method can improve performance significantly, including tasks in diffusion-based sampling, transition path sampling, and fine-tuning of diffusion models.}, language = {en} } @article{ReussMacdonaldBeckeretal.2025, author = {Reuss, Joana and Macdonald, Jan and Becker, Simon and Richter, Lorenz and K{\"o}rner, Marco}, title = {The EuroCropsML time series benchmark dataset for few-shot crop type classification in Europe}, volume = {12}, journal = {Scientific Data}, doi = {10.1038/s41597-025-04952-7}, year = {2025}, abstract = {We introduce EuroCropsML, an analysis-ready remote sensing dataset based on the open-source EuroCrops collection, for machine learning (ML) benchmarking of time series crop type classification in Europe. It is the first time-resolved remote sensing dataset designed to benchmark transnational few-shot crop type classification algorithms that supports advancements in algorithmic development and research comparability. It comprises 706683 multi-class labeled data points across 176 crop classes. Each data point features a time series of per-parcel median pixel values extracted from Sentinel-2 L1C data and precise geospatial coordinates. EuroCropsML is publicly available on Zenodo.}, language = {en} } @article{EigenLadenburgerBrenceetal.2025, author = {Eigen, Lennart and Ladenburger, Pius and Brence, Blaž and Shubitidze, Ani and Baum, Daniel and Hildebrandt, Thomas and Brecht, Michael}, title = {Elephant trunk tip musculature reflects species differences in grasping behavior}, volume = {8}, journal = {Communications Biology}, doi = {10.1038/s42003-025-08998-6}, year = {2025}, abstract = {Elephants use their trunks, muscular hydrostats, to perform a plethora of tasks. Trunk tip morphology as well as grasping behavior differ between elephant species. While African savanna elephants (Loxodonta africana) use their dorsal and ventral finger for pinching movements, Asian elephants (Elephas maximus) prefer to wrap around objects with their one dorsal finger and ventral bulb trunk tip lip. Moreover, E. maximus can flip their ventral bulb backwards to clamp objects behind the trunk tip. Whether trunk tip musculature differs between elephant species and muscle architecture is reflected by preferred grasping behavior is, however, not clear. In this study, we performed dense muscle fascicle reconstruction of three L. africana and three E. maximus hemi-trunk tips using a combination of manual and automated segmentation of high-resolution microfocus tomography (microCT) scans. We distinguish three types of muscle fascicles: longitudinal (bending and shortening), radial (elongating) and transversal muscle fascicles (elongating). We found that trunk tips of L. africana consist to one third of longitudinal and two thirds radial/transversal muscle fascicles, likely aiding in their grasping behavior, while E. maximus trunk tips consist to two thirds of longitudinal and one third radial/transversal muscle fascicles, which is advantageous for their wrapping and backward clamping behavior.}, language = {en} } @article{BrenceWandeltWalteretal.2025, author = {Brence, Blaž and Wandelt, Laura R. and Walter, Sophie and Sigrist, Stephan J. and Petzoldt, Astrid G. and Baum, Daniel}, title = {Semi-automatic 3D-quantification of in-vivo synapse formation}, journal = {ResearchSquare}, doi = {10.21203/rs.3.rs-6073150/v1}, year = {2025}, abstract = {Background: Synapses, as specialised cell-cell contacts, allow for a faithful and controlled signal transmission between a neuron and a target cell. Presynapses, the sites of neurotransmitter release, form de novo throughout the development of an organism. Although this process is fundamental to the development and function of synaptic circuits, how developing neurons control number and distribution of individual synapses remains poorly understood. In-vivo imaging analysis of synapse formation at the neuromuscular junction of anaesthetised Drosophila third instar larvae allows for spatial and temporal resolution of the underlying molecular processes. However, high-throughput, comprehensive analysis are hampered by the manual and time-consuming imaging analysis methods applied hitherto. Here, we focus on the early presynaptic formation steps, that is, the presynaptic seeding, initiated by the formation of transient Liprin-a/SYD1 seeding sites, either stabilised or disintegrated over a time span of 30-90 min. Results: To investigate the dynamics of the Liprin-a/SYD1 seeding sites, we developed an automated analysis pipeline for 3D confocal images from in-vivo imaging at distinct time points to analyse fluorescently labelled presynaptic protein dynamics during early synapse formation. The workflow is realised in the data analysis software Amira, utilising the hierarchical watershed algorithm, and was designed for automatic processing with an option for manual proofreading. Compared to the previous 2D manual quantification, this automated approach provides a higher sensitivity in single Liprin-a seeding site detection in low-intensity areas and in regions of dense seeding sites.In addition, it substantially reduces the work time. To account for possible errors occurring in the automated processing, we implemented an additional proofreading step allowing for a manual correction of Liprin-a seeding site segmentation and assignment, thus greatly improving the analysis while only marginally increasing work time by 10\% to a total work time reduction of 80\% compared to the 2D manual analysis paradigm. Conclusion: The process of synaptogenesis underlies the general principles of locomotion, learning and memory formation. The developed fast and accurate semi-automated 3D workflow provides a substantial progress in the analysis of this molecular process and its application can be easily extended to other dynamic in-vivo research approaches across species.}, language = {en} } @article{BrenceBrummerDercksenetal.2025, author = {Brence, Blaž and Brummer, Josephine and Dercksen, Vincent J. and {\"O}zel, Mehmet Neset and Kulkarni, Abhishkek and Wolterhoff, Neele and Prohaska, Steffen and Hiesinger, Peter Robin and Baum, Daniel}, title = {Semi-automatic Geometrical Reconstruction and Analysis of Filopodia Dynamics in 4D Two-Photon Microscopy Images}, journal = {bioRxiv}, doi = {10.1101/2025.05.20.654789}, year = {2025}, abstract = {Background: Filopodia are thin and dynamic membrane protrusions that play a crucial role in cell migration, axon guidance, and other processes where cells explore and interact with their surroundings. Historically, filopodial dynamics have been studied in great detail in 2D in cultured cells, and more recently in 3D culture as well as living brains. However, there is a lack of efficient tools to trace and track filopodia in 4D images of complex brain cells. Results: To address this issue, we have developed a semi-automatic workflow for tracing filopodia in 3D images and tracking the traced filopodia over time. The workflow was developed based on high-resolution data of photoreceptor axon terminals in the in vivo context of normal Drosophila brain development, but devised to be applicable to filopodia in any system, including at different temporal and spatial scales. In contrast to the pre-existing methods, our workflow relies solely on the original intensity images without the requirement for segmentation or complex preprocessing. The workflow was realized in C++ within the Amira software system and consists of two main parts, dataset pre-processing, and geometrical filopodia reconstruction, where each of the two parts comprises multiple steps. In this paper, we provide an extensive workflow description and demonstrate its versatility for two different axo-dendritic morphologies, R7 and Dm8 cells. Finally, we provide an analysis of the time requirements for user input and data processing. Conclusion: To facilitate simple application within Amira or other frameworks, we share the source code, which is available athttps://github.com/zibamira/filopodia-tool.}, language = {en} } @inproceedings{BrenceFuchsHiesingeretal.2025, author = {Brence, Blaž and Fuchs, Joachim and Hiesinger, Peter Robin and Baum, Daniel}, title = {Fully automated quantification of synaptic locations in multi-channel Drosophila photoreceptor microscopy data}, booktitle = {Eurographics Workshop on Visual Computing for Biology and Medicine}, editor = {Garrison, Laura and Krueger, Robert}, doi = {10.2312/vcbm.20251254}, year = {2025}, abstract = {The workload posed by image analysis remains a major bottleneck for advances across the life sciences. To address this challenge, we have developed a fully automated workflow for processing complex 3D multi-channel microscopy images. Specifically, our workflow addresses the analysis of photoreceptor synapses in confocal images of the Drosophila melanogaster optic lobe. The workflow consists of multiple stages, combining traditional and machine learning-based approaches for image analysis and visual computing. It performs segmentation of brain regions, photoreceptor instance identification, and precise localization of synapses. The key novelty of the workflow is an automatic alignment of synapses into a cylindrical reference coordinate system, enabling comparative synaptic analysis across photoreceptors. To demonstrate the workflow's applicability, preliminary biological results and their interpretation based on 50 images are presented. While the workflow is still being improved further, here, we showcase its capacity for efficient and objective data processing for high-throughput neurobiological analyses.}, language = {en} } @article{TrepczynskiKneifelHeylandetal.2025, author = {Trepczynski, Adam and Kneifel, Paul and Heyland, Mark and Leskovar, Marko and Moewis, Philippe and Damm, Philipp and Taylor, William R. and Zachow, Stefan and Duda, Georg N.}, title = {Impact of the external knee flexion moment on patello-femoral loading derived from in vivo loads and kinematics}, volume = {12/2024}, journal = {Frontiers in Bioengineering and Biotechnology}, publisher = {Frontiers Media SA}, organization = {Charit{\´e} - Universit{\"a}tsmedizin Berlin}, issn = {2296-4185}, doi = {10.3389/fbioe.2024.1473951}, year = {2025}, abstract = {Introduction: Anterior knee pain and other patello-femoral (PF) complications frequently limit the success of total knee arthroplasty as the final treatment of end stage osteoarthritis. However, knowledge about the in-vivo loading conditions at the PF joint remains limited, as no direct measurements are available. We hypothesised that the external knee flexion moment (EFM) is highly predictive of the PF contact forces during activities with substantial flexion of the loaded knee. Materials and methods: Six patients (65-80 years, 67-101 kg) with total knee arthroplasty (TKA) performed two activities of daily living: sit-stand-sit and squat. Tibio-femoral (TF) contact forces were measured in vivo using instrumented tibial components, while synchronously internal TF and PF kinematics were captured with mobile fluoroscopy. The measurements were used to compute PF contact forces using patient specific musculoskeletal models. The relationship between the EFM and the PF contact force was quantified using linear regression. Results: Mean peak TF contact forces of 1.97-3.24 times body weight (BW) were found while peak PF forces reached 1.75 to 3.29 times body weight (BW). The peak EFM ranged from 3.2 to 5.9 \%BW times body height, and was a good predictor of the PF contact force (R2 = 0.95 and 0.88 for sit-stand-sit and squat, respectively). Discussion: The novel combination of in vivo TF contact forces and internal patellar kinematics enabled a reliable assessment of PF contact forces. The results of the regression analysis suggest that PF forces can be estimated based solely on the EFM from quantitative gait analysis. Our study also demonstrates the relevance of PF contact forces, which reach magnitudes similar to TF forces during activities of daily living.}, language = {en} } @misc{PedersenLindnerRehfeldtetal.2025, author = {Pedersen, Jaap and Lindner, Niels and Rehfeldt, Daniel and Koch, Thorsten}, title = {Comparing Branching Rules for the Quota Steiner Tree Problem with Interference}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-101250}, year = {2025}, abstract = {Branching decisions play a crucial role in branch-and-bound algorithms for solving combinatorial optimization problems. In this paper, we investigate several branching rules applied to the Quota Steiner Tree Problem with Interference (QSTPI). The Quota Steiner Tree Problem (QSTP) generalizes the classical Steiner Tree Problem (STP) in graphs by seeking a minimum-cost tree that connects a subset of profit-associated vertices to meet a given quota. The extended version, QSTPI, introduces interference among vertices: Selecting certain vertices simultaneously reduces their individual contributions to the overall profit. This problem arises, for example, in positioning and connecting wind turbines, where turbines possibly shadow other turbines, reducing their energy yield. While exact solvers for standard STP-related problems often rely heavily on reduction techniques and cutting-plane methods - rarely generating large branch-and-bound trees - experiments reveal that large instances of QSTPI require significantly more branching to compute provably optimal solutions. In contrast to branching on variables, we utilize the combinatorial structure of the QSTPI by branching on the graph's vertices. We adapt classical and problem-specific branching rules and present a comprehensive computational study comparing the effectiveness of these branching strategies.}, language = {en} } @misc{MehlLindnerBartoszuketal.2025, author = {Mehl, Lukas and Lindner, Niels and Bartoszuk, Karolina and Zittel, Janina}, title = {Prototypical warm-starts for demand-robust LP-based energy system optimization}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-101242}, year = {2025}, abstract = {The expressiveness of energy system optimization models (ESOMs) depends on a multitude of exogenous parameters. For example, sound estimates of the future energy demand are essential to enable qualified decisions on long-term investments. However, the enormous demand fluctuations even on a fine-grained scale diminish the computational performance of large-scale ESOMs. We therefore propose a clustering-and-decomposition method for linear programming based ESOMs that first identifies and solves prototypical demand scenarios with the dual simplex algorithm, and then composes dual optimal prototype bases to a warm-start basis for the full model. We evaluate the feasibility and computational efficiency our approach on a real-world case study, using a sector-coupled ESOM with hourly resolution for the Berlin-Brandenburg area in Germany, based on the oemof framework.}, language = {en} } @misc{LindnerLiebchen2025, author = {Lindner, Niels and Liebchen, Christian}, title = {A two-stage model for periodic timetabling with fixed line activities}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-101234}, year = {2025}, abstract = {The timetable is a central pillar of any public transportation system. Constructing and optimizing periodic timetables in terms of passenger comfort and operational efficiency leads to NP-hard optimization problems that are also computationally challenging in applications. The Periodic Event Scheduling Problem (PESP) as standard mathematical tool benefits from its succinct formulation and rich combinatorial structure, but suffers from poor linear programming relaxations and weak dual bounds. These difficulties persist in a reduced version, where driving and dwelling activities of the lines are assumed to be fixed. In this case, fixing the initial departure time of each line fully determines the timetable, and for each pair of lines, the resulting (weighted) transfer durations can be expressed in terms of a piecewise linear non-convex function in terms of the difference of the initial times. When the number of activities between two lines is bounded, this function can be computed in polynomial time. By inserting precomputed piecewise linear functions into a mixed-integer program with the initial departure times as variables, we introduce an equivalent formulation for reduced PESP instances. The model bears analogies with quadratic semi-assignment approaches and offers alternative ways to compute primal and dual bounds. We evaluate the computational behavior of our approach on realistic benchmarking instances.}, language = {en} } @article{RongChenMaetal.2025, author = {Rong, Guoyang and Chen, Ying and Ma, Feicheng and Koch, Thorsten}, title = {Exploring Interdisciplinary Research Trends through Critical Years for Interdisciplinary Citation}, volume = {19}, journal = {Journal of Informetrics}, number = {4}, doi = {10.1016/j.joi.2025.101726}, year = {2025}, language = {en} } @article{ShinanoFujii2025, author = {Shinano, Yuji and Fujii, Koichi}, title = {Introduction to Quadratic Programming Solvers}, volume = {64}, journal = {Journal of The Society of Instrument and Control Engineers}, number = {8}, doi = {10.11499/sicejl.64.532}, pages = {532 -- 540}, year = {2025}, language = {en} } @inproceedings{HammerschmidtPlockBurgeretal.2025, author = {Hammerschmidt, Martin and Plock, Matthias and Burger, Sven and Truong, Vinh and Soltwisch, Victor and Schneider, Philipp-Immanuel}, title = {Machine learning approach for full Bayesian parameter reconstruction}, volume = {13568}, booktitle = {Proc. SPIE}, doi = {10.1117/12.3062268}, pages = {1356806}, year = {2025}, language = {en} } @inproceedings{SekulicSchneiderHammerschmidtetal.2025, author = {Sekulic, Ivan and Schneider, Philipp-Immanuel and Hammerschmidt, Martin and Schaible, Jonas and Burger, Sven}, title = {Physics informed Bayesian optimization for inverse design of diffractive optical elements}, volume = {PC13573}, booktitle = {Proc. SPIE}, doi = {10.1117/12.3064372}, pages = {PC135730R}, year = {2025}, language = {en} } @article{BauerGaltungGesericketal.2025, author = {Bauer, Wolfgang and Galtung, Noa and Geserick, Peter and Friedrich, Katharina and Weber, Marcus and Somasundaram, Rajan and Diehl-Wiesenecker, Eva and Kappert, Kai}, title = {Pentraxin-3, MyD88, GLP-1, and PD-L1: Performance assessment and composite algorithmic analysis for sepsis identification}, volume = {91}, journal = {Journal of Infection}, number = {3}, doi = {10.1016/j.jinf.2025.106599}, pages = {106599}, year = {2025}, abstract = {This study examines nine emerging biomarkers as possible indicators for diagnosing sepsis in emergency department patient.}, language = {en} } @article{KourovSamoilovaStraube2025, author = {Kourov, Mikhail N. and Samoilova, Anna E. and Straube, Arthur}, title = {Dynamics of a chain of interacting magnetic particles in a one-dimensional periodic energy landscape}, volume = {89}, journal = {Bull. Russ. Acad. Sci. Phys.}, number = {7}, issn = {1062-8738}, doi = {10.1134/S1062873825711742}, pages = {1086 -- 1092}, year = {2025}, abstract = {We explore the dynamics of a one-dimensional chain of paramagnetic colloidal particles in a periodic potential. The model accounts for a constant external force, along with magnetic dipolar attraction and hard-core repulsive interactions between particles. Numerical simulations reveal the emergence of a traveling kink - a chain defect propagating along the chain. We show that the kink emerges beyond a critical force threshold and identify parameter regimes corresponding to distinct dynamic modes such as a pinned kink, a running kink, a cluster kink, and chain drift.}, language = {en} } @article{StraubeOliconMendezWinkelmannetal.2025, author = {Straube, Arthur and Olic{\´o}n M{\´e}ndez, Guillermo and Winkelmann, Stefanie and H{\"o}fling, Felix and Engel, Maximilian}, title = {Unfolding the geometric structure and multiple timescales of the urea-urease pH oscillator}, arxiv = {http://arxiv.org/abs/2508.07275}, year = {2025}, abstract = {We study a two-variable dynamical system modeling pH oscillations in the urea-urease reaction within giant lipid vesicles - a problem that intrinsically contains multiple, well-separated timescales. Building on an existing, deterministic formulation via ordinary differential equations, we resolve different orders of magnitude within a small parameter and analyze the system's limit cycle behavior using geometric singular perturbation theory (GSPT). By introducing two different coordinate scalings - each valid in a distinct region of the phase space - we resolve the local dynamics near critical fold points, using the extension of GSPT through such singular points due to Krupa and Szmolyan. This framework enables a geometric decomposition of the periodic orbits into slow and fast segments and yields closed-form estimates for the period of oscillation. In particular, we link the existence of such oscillations to an underlying biochemical asymmetry, namely, the differential transport across the vesicle membrane.}, language = {en} } @inproceedings{RiedmuellerZittelKoch2026, author = {Riedm{\"u}ller, Stephanie and Zittel, Janina and Koch, Thorsten}, title = {Warm-starting Strategies in Scalarization Methods for Multi-Objective Optimization}, booktitle = {Operations Research Proceedings 2025}, arxiv = {http://arxiv.org/abs/2507.21933}, year = {2026}, abstract = {We explore how warm-starting strategies can be integrated into scalarization-based approaches for multi-objective optimization in (mixed) integer linear programming. Scalarization methods remain widely used classical techniques to compute Pareto-optimal solutions in applied settings. They are favored due to their algorithmic simplicity and broad applicability across continuous and integer programs with an arbitrary number of objectives. While warm-starting has been applied in this context before, a systematic methodology and analysis remain lacking. We address this gap by providing a theoretical characterization of warm-starting within scalarization methods, focusing on the sequencing of subproblems. However, optimizing the order of subproblems to maximize warm-start efficiency may conflict with alternative criteria, such as early identification of infeasible regions. We quantify these trade-offs through an extensive computational study.}, language = {en} } @misc{RiedmuellerZittelKoch2025, author = {Riedm{\"u}ller, Stephanie and Zittel, Janina and Koch, Thorsten}, title = {Warm-starting Strategies in Scalarization Methods for Multi-Objective Optimization}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-101073}, year = {2025}, abstract = {We explore how warm-starting strategies can be integrated into scalarization-based approaches for multi-objective optimization in (mixed) integer linear programming. Scalarization methods remain widely used classical techniques to compute Pareto-optimal solutions in applied settings. They are favored due to their algorithmic simplicity and broad applicability across continuous and integer programs with an arbitrary number of objectives. While warm-starting has been applied in this context before, a systematic methodology and analysis remain lacking. We address this gap by providing a theoretical characterization of warm-starting within scalarization methods, focusing on the sequencing of subproblems. However, optimizing the order of subproblems to maximize warm-start efficiency may conflict with alternative criteria, such as early identification of infeasible regions. We quantify these trade-offs through an extensive computational study.}, language = {en} } @misc{BinkowskiKoulasSimosBetzetal.2025, author = {Binkowski, Felix and Koulas-Simos, Aris and Betz, Fridtjof and Plock, Matthias and Sekulic, Ivan and Manley, Phillip and Hammerschmidt, Martin and Schneider, Philipp-Immanuel and Zschiedrich, Lin and Munkhbat, Battulga and Reitzenstein, Stephan and Burger, Sven}, title = {Source code and simulation results: High Purcell enhancement in all-TMDC nanobeam resonator designs with active monolayers for nanolasers}, journal = {Zenodo}, doi = {10.5281/zenodo.16533803}, year = {2025}, language = {en} } @article{BinkowskiKoulasSimosBetzetal.2025, author = {Binkowski, Felix and Koulas-Simos, Aris and Betz, Fridtjof and Plock, Matthias and Sekulic, Ivan and Manley, Phillip and Hammerschmidt, Martin and Schneider, Philipp-Immanuel and Zschiedrich, Lin and Munkhbat, Battulga and Reitzenstein, Stephan and Burger, Sven}, title = {High Purcell enhancement in all-TMDC nanobeam resonator designs with active monolayers for nanolasers}, volume = {112}, journal = {Phys. Rev. B}, arxiv = {http://arxiv.org/abs/2508.05333}, doi = {10.1103/nxh9-dhvx}, pages = {235410}, year = {2025}, language = {en} } @article{WeimannConrad2025, author = {Weimann, Kuba and Conrad, Tim}, title = {Self-supervised pre-training with joint-embedding predictive architecture boosts ECG classification performance}, volume = {196}, journal = {Computers in Biology and Medicine}, publisher = {Elsevier BV}, issn = {0010-4825}, doi = {10.1016/j.compbiomed.2025.110809}, year = {2025}, abstract = {Accurate diagnosis of heart arrhythmias requires the interpretation of electrocardiograms (ECG), which capture the electrical activity of the heart. Automating this process through machine learning is challenging due to the need for large annotated datasets, which are difficult and costly to collect. To address this issue, transfer learning is often employed, where models are pre-trained on large datasets and fine-tuned for specific ECG classification tasks with limited labeled data. Self-supervised learning has become a widely adopted pre-training method, enabling models to learn meaningful representations from unlabeled datasets. In this work, we explore the joint-embedding predictive architecture (JEPA) for self-supervised learning from ECG data. Unlike invariance-based methods, JEPA does not rely on hand-crafted data augmentations, and unlike generative methods, it predicts latent features rather than reconstructing input data. We create a large unsupervised pre-training dataset by combining ten public ECG databases, amounting to over one million records. We pre-train Vision Transformers using JEPA on this dataset and fine-tune them on various PTB-XL benchmarks. Our results show that JEPA outperforms existing invariance-based and generative approaches, achieving an AUC of 0.945 on the PTB-XL all statements task. JEPA consistently learns the highest quality representations, as demonstrated in frozen evaluations, and proves advantageous for pre-training even in the absence of additional data.}, language = {en} } @inproceedings{FayadZimmerSchwartzetal.2025, author = {Fayad, Ibrahim and Zimmer, Max and Schwartz, Martin and Ciais, Philippe and Gieseke, Fabian and Belouze, Gabriel and Brood, Sarah and De Truchis, Aurelien and d'Aspremont, Alexandre}, title = {DUNIA: Pixel-Sized Embeddings via Cross-Modal Alignment for Earth Observation Applications}, volume = {267}, booktitle = {Proceedings of the 42nd International Conference on Machine Learning}, arxiv = {http://arxiv.org/abs/2502.17066}, pages = {16375 -- 16406}, year = {2025}, language = {en} } @inproceedings{PaulsZimmerTuranetal.2025, author = {Pauls, Jan and Zimmer, Max and Turan, Berkant and Saatchi, Sassan and Ciais, Philippe and Pokutta, Sebastian and Gieseke, Fabian}, title = {Capturing Temporal Dynamics in Large-Scale Canopy Tree Height Estimation}, volume = {267}, booktitle = {Proceedings of the 42nd International Conference on Machine Learning}, arxiv = {http://arxiv.org/abs/2501.19328}, pages = {48422 -- 48438}, year = {2025}, language = {en} } @article{KlusGelss2025, author = {Klus, Stefan and Gelß, Patrick}, title = {Continuous optimization methods for the graph isomorphism problem}, volume = {14}, journal = {Information and Inference: A Journal of the IMA}, number = {2}, doi = {10.1093/imaiai/iaaf011}, year = {2025}, language = {en} } @inproceedings{MundingerZimmerKiemetal.2025, author = {Mundinger, Konrad and Zimmer, Max and Kiem, Aldo and Spiegel, Christoph and Pokutta, Sebastian}, title = {Neural Discovery in Mathematics: Do Machines Dream of Colored Planes?}, volume = {267}, booktitle = {Proceedings of the 42nd International Conference on Machine Learning}, arxiv = {http://arxiv.org/abs/2501.18527}, pages = {45236 -- 45255}, year = {2025}, language = {en} } @inproceedings{PelleritiZimmerWirthetal.2025, author = {Pelleriti, Nico and Zimmer, Max and Wirth, Elias and Pokutta, Sebastian}, title = {Approximating Latent Manifolds in Neural Networks via Vanishing Ideals}, volume = {267}, booktitle = {Proceedings of the 42nd International Conference on Machine Learning}, arxiv = {http://arxiv.org/abs/2502.15051}, pages = {48734 -- 48761}, year = {2025}, language = {en} } @inproceedings{RouxMartinezRubioPokutta2025, author = {Roux, Christophe and Mart{\´i}nez-Rubio, David and Pokutta, Sebastian}, title = {Implicit Riemannian optimism with applications to min-max problems}, volume = {267}, booktitle = {Proceedings of the 42nd International Conference on Machine Learning}, arxiv = {http://arxiv.org/abs/2501.18381}, pages = {52139 -- 52172}, year = {2025}, language = {en} } @inproceedings{TuranAsadullaSteinmannetal.2025, author = {Turan, Berkant and Asadulla, Suhrab and Steinmann, David and Stammer, Wolfgang and Pokutta, Sebastian}, title = {Neural Concept Verifier: Scaling Prover-Verifier Games via Concept Encodings}, booktitle = {Proceedings of the ICML Workshop on Actionable Interpretability}, year = {2025}, language = {en} } @inproceedings{XuMexiBestuzheva2025, author = {Xu, Liding and Mexi, Gioni and Bestuzheva, Ksenia}, title = {Sparsity-driven Aggregation of Mixed Integer Programs}, volume = {338}, booktitle = {23rd International Symposium on Experimental Algorithms (SEA 2025)}, address = {Schloss Dagstuhl - Leibniz-Zentrum f{\"u}r Informatik}, doi = {10.4230/LIPIcs.SEA.2025.27}, pages = {27:1 -- 27:15}, year = {2025}, language = {en} } @inproceedings{HendrychBesanconMartinezRubioetal.2025, author = {Hendrych, Deborah and Besan{\c{c}}on, Mathieu and Mart{\´i}nez-Rubio, David and Pokutta, Sebastian}, title = {Secant line search for Frank-Wolfe algorithms}, volume = {267}, booktitle = {Proceedings of the 42nd International Conference on Machine Learning}, arxiv = {http://arxiv.org/abs/2501.18775}, pages = {23005 -- 23029}, year = {2025}, language = {en} } @inproceedings{HaaseHanelPokutta2025, author = {Haase, Jennifer and Hanel, Paul H. P. and Pokutta, Sebastian}, title = {S-DAT: a multilingual, GenAI-driven framework for automated divergent thinking assessment}, volume = {8}, booktitle = {Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society (AIES)}, pages = {1194 -- 1205}, year = {2025}, language = {en} } @article{GelssKleinMateraetal.2025, author = {Gelß, Patrick and Klein, Rupert and Matera, Sebastian and Schmidt, Burkhard}, title = {Quantum dynamics of coupled excitons and phonons in chain-like systems: tensor train approaches and higher-order propagators}, volume = {162}, journal = {The Journal of Chemical Physics}, doi = {10.1063/5.0258904}, year = {2025}, language = {en} } @article{WirthPenaPokutta2025, author = {Wirth, Elias and Pe{\~n}a, Javier and Pokutta, Sebastian}, title = {Fast convergence of Frank-Wolfe algorithms on polytopes}, journal = {INFORMS Journal on Mathematics of Operations Research}, doi = {10.1287/moor.2024.0580}, year = {2025}, language = {en} } @article{RamosFischerSaalfranketal.2024, author = {Ramos, Alejandro and Fischer, Eric W. and Saalfrank, Peter and K{\"u}hn, Oliver}, title = {Shaping the laser control landscape of a hydrogen transfer reaction by vibrational strong coupling. A direct optimal control approach}, journal = {The Journal of Chemical Physics}, year = {2024}, language = {en} } @article{HalbigHoenGleixneretal.2025, author = {Halbig, Katrin and Hoen, Alexander and Gleixner, Ambros and Witzig, Jakob and Weninger, Dieter}, title = {A diving heuristic for mixed-integer problems with unbounded semi-continuous variables}, volume = {13}, journal = {EURO Journal on Computational Optimization}, doi = {10.1016/j.ejco.2025.100107}, year = {2025}, language = {en} } @inproceedings{UrbanoRomero2024, author = {Urbano, Alonso and Romero, David W.}, title = {Self-Supervised Detection of Perfect and Partial Input-Dependent Symmetries}, booktitle = {Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM) at ICML 2024}, year = {2024}, language = {en} } @incollection{ZimmerSpiegelPokutta2025, author = {Zimmer, Max and Spiegel, Christoph and Pokutta, Sebastian}, title = {Compression-aware training of neural networks using Frank-Wolfe}, booktitle = {Mathematical Optimization for Machine Learning: Proceedings of the MATH+ Thematic Einstein Semester 2023}, editor = {Fackeldey, K.}, publisher = {De Gruyter}, doi = {10.1515/9783111376776-010}, pages = {137 -- 168}, year = {2025}, language = {en} } @article{RamosKuehn2022, author = {Ramos, Alejandro and K{\"u}hn, Oliver}, title = {Manipulating the dynamics of a Fermi resonance with light. A direct optimal control theory approach}, journal = {Chemical Physics}, year = {2022}, language = {en} } @article{WidlerKaminskaMartinsetal.2026, author = {Widler, Valeria and Kaminska, Barbara and Martins, Andre C. R. and Puga-Gonzalez, Ivan}, title = {An Investigation into the Causal Mechanism of Political Opinion Dynamics: A Model of Hierarchical Coarse-Graining with Community-Bounded Social Influence}, journal = {Computational Social Science of Social Cohesion and Polarization}, edition = {Computational Social Science of Social Cohesion and Polarization}, publisher = {Springer, Cham.}, arxiv = {http://arxiv.org/abs/2504.00877}, doi = {10.1007/978-3-032-01373-6_10}, pages = {225 -- 256}, year = {2026}, abstract = {The increasing polarization in democratic societies is an emergent outcome of political opinion dynamics. Yet, the fundamental mechanisms behind the formation of political opinions, from individual beliefs to collective consensus, remain unknown. Understanding that a causal mechanism must account for both bottom-up and top-down influences, we conceptualize political opinion dynamics as hierarchical coarse-graining, where microscale opinions integrate into a macro-scale state variable. Using the CODA (Continuous Opinions Discrete Actions) model, we simulate Bayesian opinion updating, social identity-based information integration, and migration between social identity groups to represent higher-level connectivity. This results in coarse-graining across micro, meso, and macro levels. Our findings show that higher-level connectivity shapes information integration, yielding three regimes: independent (disconnected, local convergence), parallel (fast, global convergence), and iterative (slow, stepwise convergence). In the iterative regime, low connectivity fosters transient diversity, indicating an informed consensus. In all regimes, time-scale separation leads to downward causation, where agents converge on the aggregate majority choice, driving consensus. Critically, any degree of coherent higher-level information integration can overcome misalignment via global downward causation. The results highlight how emergent properties of the causal mechanism, such as downward causation, are essential for consensus and may inform more precise investigations into polarized political discourse.}, language = {en} }