TY - CHAP A1 - Stompor, Tomasz A1 - Zittel, Janina A1 - Koch, Thorsten A1 - Rusch, Beate T1 - Fully Algorithmic Librarian: Large-Scale Citation Experiments T2 - 20th International Society of Scientometrics and Informetrics Conference 2025, June 23-27, 2025 | Yerevan, Armenia N2 - The Fully Algorithmic Librarian (FAN) project explores application scenarios for algorithmic-intelligence(AI)-supported methods in academic libraries as central institutions for research support. To this end, the study builds on two algorithmic approaches for analyzing large-scale citation networks. A comparison of Web of Science (WoS) and OpenAlex structures using the PageRank algorithm reveals key differences. Additionally, a multi-label clustering technique designed for large-scale citation networks accounts for disciplinary variations in publication practices. Y1 - 2025 U6 - https://doi.org/10.51408/issi2025_204 ER - TY - JOUR A1 - Chen, Ying A1 - Koch, Thorsten A1 - Peng, Hanqui A1 - Zhang, Hongrui T1 - Benchmarking of Quantum and Classical Computing in Large-Scale Dynamic Portfolio Optimization Under Market Frictions Y1 - 2025 ER - TY - JOUR A1 - Jäger, Klaus A1 - Aeberhard, Urs A1 - Alarcon Llado, Esther A1 - Bläsi, Benedikt A1 - Burger, Sven A1 - Ehrler, Bruno A1 - Favre, Wilfried A1 - Fejfar, Antonín A1 - Gageot, Tristan A1 - Gordon, Ivan A1 - Helmers, Henning A1 - Höhn, Oliver A1 - Isabella, Olindo A1 - Jošt, Marko A1 - Ledinský, Martin A1 - Mandal, Jyotirmoy A1 - Manley, Phillip A1 - Muñoz, Delfina A1 - Omair, Zunaid A1 - Ortiz Lizcano, Juan Camilo A1 - Paetzold, Ulrich W. A1 - Raman, Aaswath P. A1 - Sai, Hitoshi A1 - Saive, Rebecca A1 - Schmid, Martina A1 - Yablonovitch, Eli A1 - Becker, Christiane T1 - Optics for terawatt-scale photovoltaics: review and perspectives JF - Adv. Opt. Photonics N2 - Photovoltaics, a mature technology, is set to play a vital role in achieving a carbon-free energy system. This article examines the pivotal role of optics in advancing photovoltaics. We identify key scientific research areas where the optics community can make significant contributions. We are guided by the central question: How can optics facilitate the large-scale deployment of photovoltaics necessary for decarbonizing our societies? Y1 - 2025 U6 - https://doi.org/10.1364/AOP.530556 SN - 1943-8206 VL - 17 IS - 1 SP - 185 EP - 294 PB - Optica Publishing Group ER - TY - JOUR A1 - Wirth, Elias A1 - Pena, Javier A1 - Pokutta, Sebastian T1 - Correction: Accelerated affine-invariant convergence rates of the Frank-Wolfe algorithm with open-loop step-sizes JF - Mathematical Programming Y1 - 2025 U6 - https://doi.org/10.1007/s10107-025-02214-3 VL - 214 SP - 941 EP - 942 ER - TY - CHAP A1 - Roux, Christophe A1 - Zimmer, Max A1 - Pokutta, Sebastian T1 - On the byzantine-resilience of distillation-based federated learning T2 - 13th International Conference on Learning Representations (ICLR 2025) N2 - Federated Learning (FL) algorithms using Knowledge Distillation (KD) have received increasing attention due to their favorable properties with respect to privacy, non-i.i.d. data and communication cost. These methods depart from transmitting model parameters and instead communicate information about a learning task by sharing predictions on a public dataset. In this work, we study the performance of such approaches in the byzantine setting, where a subset of the clients act in an adversarial manner aiming to disrupt the learning process. We show that KD-based FL algorithms are remarkably resilient and analyze how byzantine clients can influence the learning process. Based on these insights, we introduce two new byzantine attacks and demonstrate their ability to break existing byzantine-resilient methods. Additionally, we propose a novel defence method which enhances the byzantine resilience of KD-based FL algorithms. Finally, we provide a general framework to obfuscate attacks, making them significantly harder to detect, thereby improving their effectiveness. Y1 - 2025 UR - https://openreview.net/pdf?id=of6EuHT7de ER - TY - CHAP A1 - Sadiku, Shpresim A1 - Wagner, Moritz A1 - Nagarajan, Sai Ganesh A1 - Pokutta, Sebastian T1 - S-CFE: Simple Counterfactual Explanations T2 - Proceedings of The 28th International Conference on Artificial Intelligence and Statistics Y1 - 2025 UR - https://raw.githubusercontent.com/mlresearch/v258/main/assets/sadiku25a/sadiku25a.pdf VL - 258 SP - 172 EP - 180 ER - TY - JOUR A1 - Woodstock, Zev A1 - Pokutta, Sebastian T1 - Splitting the conditional gradient algorithm JF - SIAM Journal on Optimization Y1 - 2025 U6 - https://doi.org/10.1137/24M1638008 VL - 35 IS - 1 SP - 347 EP - 368 ER - TY - CHAP A1 - Głuch, Grzegorz A1 - Turan, Berkant A1 - Nagarajan, Sai Ganesh A1 - Pokutta, Sebastian T1 - The good, the bad and the ugly: watermarks, transferable attacks and adversarial defenses T2 - 1st Workshop on GenAI Watermarking, collocated with ICLR 2025 Y1 - 2025 UR - https://openreview.net/pdf?id=rUs5ryYqZe ER - TY - CHAP A1 - Hollender, Alexandros A1 - Maystre, Gilbert A1 - Nagarajan, Sai Ganesh T1 - The Complexity of Two-Team Polymatrix Games with Independent Adversaries T2 - 13th International Conference on Learning Representations (ICLR 2025) N2 - Adversarial multiplayer games are an important object of study in multiagent learning. In particular, polymatrix zero-sum games are a multiplayer setting where Nash equilibria are known to be efficiently computable. Towards understanding the limits of tractability in polymatrix games, we study the computation of Nash equilibria in such games where each pair of players plays either a zero-sum or a coordination game. We are particularly interested in the setting where players can be grouped into a small number of teams of identical interest. While the three-team version of the problem is known to be PPAD-complete, the complexity for two teams has remained open. Our main contribution is to prove that the two-team version remains hard, namely it is CLS-hard. Furthermore, we show that this lower bound is tight for the setting where one of the teams consists of multiple independent adversaries. On the way to obtaining our main result, we prove hardness of finding any stationary point in the simplest type of non-convex-concave min-max constrained optimization problem, namely for a class of bilinear polynomial objective functions. Y1 - 2025 UR - https://openreview.net/pdf?id=9VGTk2NYjF ER - TY - CHAP A1 - Lasby, Mike A1 - Zimmer, Max A1 - Pokutta, Sebastian A1 - Schultheis, Erik T1 - Compressed sparse tiles for memory-efficient unstructured and semi-structured sparsity T2 - Proceedings of the ICLR Workshop on Sparsity in LLMs Y1 - 2025 UR - https://openreview.net/forum?id=iso0KV2HVq ER - TY - CHAP A1 - Besançon, Mathieu A1 - Pokutta, Sebastian A1 - Wirth, Elias T1 - The Pivoting Framework: Frank-Wolfe Algorithms with Active Set Size Control T2 - Proceedings of The 28th International Conference on Artificial Intelligence and Statistics Y1 - 2025 UR - https://raw.githubusercontent.com/mlresearch/v258/main/assets/besancon25a/besancon25a.pdf VL - 258 SP - 271 EP - 279 ER - TY - CHAP A1 - Schaible, Jonas A1 - Winarto, Hanifah A1 - Skorjanc, Victor A1 - Yoo, Danbi A1 - Zimmermann, Lea A1 - Wessels, Andreas A1 - Jäger, Klaus A1 - Sekulic, Ivan A1 - Schneider, Philipp-Immanuel A1 - Bläsi, Benedikt A1 - Burger, Sven A1 - Becker, Christiane T1 - Optimization strategies for colorful thin film solar cells T2 - Proc. SPIE Y1 - 2025 U6 - https://doi.org/10.1117/12.3041408 VL - PC13361 SP - PC133610E ER - TY - JOUR A1 - Xu, Xiaofei A1 - Chen, Ying A1 - Zhang, Ge A1 - Koch, Thorsten T1 - Modeling Functional Time Series and Mixed-Type Predictors With Partially Functional Autoregressions JF - Journal of Business & Economic Statistics Y1 - 2022 U6 - https://doi.org/https://doi.org/10.1080/07350015.2021.2011299 SN - 0735-0015 VL - 42 IS - 2 SP - 349 EP - 366 PB - Informa UK Limited ER - TY - CHAP A1 - Hadjidimitriou, Natalia Selini A1 - Lippi, Marco A1 - Nastro, Raffaele A1 - Koch, Thorsten A1 - Mamei, Marco T1 - Short-Term Forecasting of Energy Consumption and Production in Local Energy Communities T2 - 2024 32nd International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE) Y1 - 2024 U6 - https://doi.org/10.1109/WETICE64632.2024.00022 SP - 74 EP - 79 PB - IEEE ER - TY - JOUR A1 - Boulanger-Weill, Jonathan A1 - Kaempf, Florian A1 - L. Schalek, Richard A1 - Petkova, Mariela A1 - Vohra, Sumit Kumar A1 - Savaliya, Jay H. A1 - Wu, Yuelong A1 - Schuhknecht, Gregor F. P. A1 - Naumann, Heike A1 - Eberle, Maren A1 - Kirchberger, Kim N. A1 - Rencken, Simone A1 - Bianco, Isaac H. A1 - Baum, Daniel A1 - Bene, Filippo Del A1 - Engert, Florian A1 - Lichtman, Jeff W. A1 - Bahl, Armin T1 - Correlative light and electron microscopy reveals the fine circuit structure underlying evidence accumulation in larval zebrafish JF - bioRxiv N2 - Accumulating information is a critical component of most circuit computations in the brain across species, yet its precise implementation at the synaptic level remains poorly understood. Dissecting such neural circuits in vertebrates requires precise knowledge of functional neural properties and the ability to directly correlate neural dynamics with the underlying wiring diagram in the same animal. Here we combine functional calcium imaging with ultrastructural circuit reconstruction, using a visual motion accumulation paradigm in larval zebrafish. Using connectomic analyses of functionally identified cells and computational modeling, we show that bilateral inhibition, disinhibition, and recurrent connectivity are prominent motifs for sensory accumulation within the anterior hindbrain. We also demonstrate that similar insights about the structure-function relationship within this circuit can be obtained through complementary methods involving cell-specific morphological labeling via photo-conversion of functionally identified neuronal response types. We used our unique ground truth datasets to train and test a novel classifier algorithm, allowing us to assign functional labels to neurons from morphological libraries where functional information is lacking. The resulting feature-rich library of neuronal identities and connectomes enabled us to constrain a biophysically realistic network model of the anterior hindbrain that can reproduce observed neuronal dynamics and make testable predictions for future experiments. Our work exemplifies the power of hypothesis-driven electron microscopy paired with functional recordings to gain mechanistic insights into signal processing and provides a framework for dissecting neural computations across vertebrates. Y1 - 2025 U6 - https://doi.org/10.1101/2025.03.14.643363 ER - TY - GEN A1 - Tesch, Alexander A1 - Borndörfer, Ralf T1 - Mathematische Optimierung in der OP-Planung T2 - OP-Management up2date N2 - Deutsche Krankenhäuser sehen sich derzeit mit enormen Schwierigkeiten konfrontiert. Ungefähr jede 2. Klinik muss drastische Sparmaßnahmen ergreifen, was auch die Allgemeinversorgung beeinträchtigt. Die Gründe dafür sind vielschichtig: stark gestiegene Sach- und Personalkosten bei gleicher Finanzierung, teilweiser Patientenrückgang, starke regionale Unterschiede in der Versorgung, Fachkräftemangel und fehlende Investitionen in Kern- und Zukunftsbereiche, insbesondere der Digitalisierung. Das belastet die Haushalte der Kliniken. Insbesondere die Digitalisierung und die Anwendung von Methoden der künstlichen Intelligenz und der mathematischen Optimierung könnten eine Schlüsselrolle spielen, um die komplexen Krankenhausprozesse mit Kennzahlen qualitativ zu bewerten und zu verbessern. In diesem Artikel stellen wir vier Praxisprobleme aus der OP-Planung vor und benennen welche Entscheidungen, Nebenbedingungen und Zielkriterien mit mathematischen Entscheidungsmodellen dargestellt und optimiert werden können. Hierzu erläutern wir das erweiterte Potenzial einer umfassenden Anwendung von mathematischer Optimierung im OP-Bereich. Y1 - 2025 U6 - https://doi.org/10.1055/a-2322-2124 VL - 5 IS - 1 SP - 21 EP - 34 PB - Thieme ER - TY - GEN A1 - Kempke, Nils-Christian A1 - Koch, Thorsten T1 - Low-precision first-order method-based fix-and-propagate heuristics for large-scale mixed-integer linear optimization N2 - We investigate the use of low-precision first-order methods (FOMs) within a fix-and-propagate (FP) framework for solving mixed-integer programming problems (MIPs). FOMs, using only matrix-vector products instead of matrix factorizations, are well suited for GPU acceleration and have recently gained more attention for their application to large-scale linear programming problems (LPs). We employ PDLP, a variant of the Primal-Dual Hybrid Gradient (PDHG) method specialized to LP problems, to solve the LP-relaxation of our MIPs to low accuracy. This solution is used to motivate fixings within our fix-and-propagate framework. We implemented four different FP variants using primal and dual LP solution information. We evaluate the performance of our heuristics on MIPLIB 2017, showcasing that the low-accuracy LP solution produced by the FOM does not lead to a loss in quality of the FP heuristic solutions when compared to a high-accuracy interior-point method LP solution. Further, we use our FP framework to produce high-accuracy solutions for large-scale (up to 243 million non-zeros and 8 million decision variables) unit-commitment energy-system optimization models created with the modeling framework REMix. For the largest problems, we can generate solutions with under 2% primal-dual gap in less than 4 hours, whereas commercial solvers cannot generate feasible solutions within two days of runtime. This study represents the first successful application of FOMs in large-scale mixed-integer optimization, demonstrating their efficacy and establishing a foundation for future research in this domain. T3 - ZIB-Report - 25-04 KW - Integer programming KW - Large scale optimization KW - Linear Programming KW - Primal heuristics KW - OR in energy Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-99612 SN - 1438-0064 ER - TY - GEN A1 - Betz, Fridtjof A1 - Binkowski, Felix A1 - Fischbach, Jan David A1 - Feldman, Nick A1 - Rockstuhl, Carsten A1 - Koenderink, A. Femius A1 - Burger, Sven T1 - Source code and simulation results: Hidden resonances in non-Hermitian systems with scattering thresholds T2 - Zenodo Y1 - 2025 U6 - https://doi.org/10.5281/zenodo.14651612 SP - doi: 10.5281/zenodo.14651612 ER - TY - JOUR A1 - Betz, Fridtjof A1 - Binkowski, Felix A1 - Fischbach, Jan David A1 - Feldman, Nick A1 - Zschiedrich, Lin A1 - Rockstuhl, Carsten A1 - Koenderink, A. Femius A1 - Burger, Sven T1 - Uncovering hidden resonances in non-Hermitian systems with scattering thresholds JF - Laser Photonics Rev. Y1 - 2025 U6 - https://doi.org/10.1002/lpor.202500811 VL - 19 SP - e00811 ER - TY - CHAP A1 - Christgau, Steffen A1 - Dylan, Everingham A1 - Lübke, Max A1 - De Lucia, Marco A1 - Puhan, Danny A1 - Schelten, Niklas A1 - Schnor, Bettina A1 - Signer, Hannes A1 - Spazier, Johannes A1 - Stabernack, Benno A1 - Steinert, Fritjof A1 - Yahdzhyiev, Serhii T1 - On the Usability and Energy Efficiency of High-Level Synthesis for FPGA-based Network-Attached Accelerators T2 - 2025 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW) N2 - Heterogeneity in high performance computing systems is one of the most promising approaches towards more energy-efficient computing on one hand and satisfying the raising demand of global computation capacity on the other hand. Besides the well-known key components like CPUs and GPGPUs are domain-specific accelerators like TPUs, FPGAs well known for their energy efficiency. This is especially true for highly specialized use cases. Network-attached accelerators promise more scalability and flexibility for FPGA usage in HPC environments. Easy and efficient programming of those accelerators is, however, still an open issue. Based on a framework for such accelerators which enables decoupling of FPGAs from their host system, we present a workflow using High-Level Synthesis (HLS) to offload application kernels to them. We evaluate this approach against a conventional Hardware Description Language (HDL) based workflow. In addition, we introduce the energy measurement tool EMA and assess the energy efficiency of both HLS and HDL design. Y1 - 2025 U6 - https://doi.org/10.1109/IPDPSW66978.2025.00139 SP - 886 EP - 895 ER - TY - JOUR A1 - Sikeler, Christoph A1 - Kempter, Susanne A1 - Sekulic, Ivan A1 - Burger, Sven A1 - Liedl, Tim T1 - Chiral Plasmonic Crystals Self-Assembled by DNA Origami JF - J. Phys. Chem. C Y1 - 2025 U6 - https://doi.org/10.1021/acs.jpcc.4c08768 VL - 129 IS - 10 SP - 5116 EP - 5121 ER - TY - GEN A1 - Kempke, Nils-Christian A1 - Kunt, Tim A1 - Katamish, Bassel A1 - Vanaret, Charlie A1 - Sasanpour, Shima A1 - Clarner, Jan-Patrick A1 - Koch, Thorsten T1 - Developing heuristic solution techniques for large-scale unit commitment models N2 - Shifting towards renewable energy sources and reducing carbon emissions necessitate sophisticated energy system planning, optimization, and extension. Energy systems optimization models (ESOMs) often form the basis for political and operational decision-making. ESOMs are frequently formulated as linear (LPs) and mixed-integer linear (MIP) problems. MIPs allow continuous and discrete decision variables. Consequently, they are substantially more expressive than LPs but also more challenging to solve. The ever-growing size and complexity of ESOMs take a toll on the computational time of state-of-the-art commercial solvers. Indeed, for large-scale ESOMs, solving the LP relaxation -- the basis of modern MIP solution algorithms -- can be very costly. These time requirements can render ESOM MIPs impractical for real-world applications. This article considers a set of large-scale decarbonization-focused unit commitment models with expansion decisions based on the REMix framework (up to 83 million variables and 900,000 discrete decision variables). For these particular instances, the solution to the LP relaxation and the MIP optimum lie close. Based on this observation, we investigate the application of relaxation-enforced neighborhood search (RENS), machine learning guided rounding, and a fix-and-propagate (FP) heuristic as a standalone solution method. Our approach generated feasible solutions 20 to 100 times faster than GUROBI, achieving comparable solution quality with primal-dual gaps as low as 1% and up to 35%. This enabled us to solve numerous scenarios without lowering the quality of our models. For some instances that Gurobi could not solve within two days, our FP method provided feasible solutions in under one hour. T3 - ZIB-Report - 25-03 KW - Energy system optimization models KW - Unit commitment KW - Mixed-integer programming KW - Large-scale optimization KW - Primal heuristics Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-99555 SN - 1438-0064 ER - TY - GEN A1 - Hasler, Tim A1 - Amrhein, Kilian A1 - Klindt, Marco A1 - Oltmanns, Elias A1 - Peters-Kottig, Wolfgang T1 - Backup ist KEINE Langzeitverfügbarkeit N2 - Diese Handreichung im Flyerformat soll mit den verschiedenen Missverständnissen aufräumen, die einem im Alltag begegnen, wenn man es mit digitaler Langzeitverfügbarkeit zu tun hat. Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-99548 ER - TY - JOUR A1 - Stompor, Tomasz A1 - Pampel, Heinz A1 - Boltze‐Fütterer, Julia A1 - Rusch, Beate T1 - DeepGreen—A Data Hub for the Distribution of Scholarly Articles From Publishers to Open Access Repositories in Germany JF - Learned Publishing N2 - DeepGreen is an automated delivery service for open access articles. Originally conceived to take advantage of the so-called open access component—a secondary publication right in Alliance and National licences in Germany to promote green open access—it aims to streamline open access processes by automating the distribution of full-text articles and metadata from publishers to repositories. The service, developed by a consortium and funded by the German Research Foundation (DFG) in its initial phase, has successfully established itself as a national service, facilitating open access content distribution and contributing to Germany's open access infrastructure. As of December 2024, DeepGreen distributes articles from 14 publishers to 84 institutional repositories and 6 subject-specific repositories. This article describes the role of the DeepGreen service in Germany, its collaboration with publishers and the potential of automated processes for storing articles in open access repositories, which, as publicly owned institutional infrastructures, ensure sustainable access and provide secure, redundant storage. KW - open access KW - open access repositories Y1 - 2025 U6 - https://doi.org/https://doi.org/10.1002/leap.70000 SN - 0953-1513 VL - 38 IS - 2 PB - Wiley ER - TY - JOUR A1 - Klasse, Sarah Michelle A1 - Weber, Marcus T1 - A Case Study of the Use of Logical Data Analysis in the Workmen’s Village in Tell el-Amarna, Egypt JF - it - Information Technology N2 - The search for patterns in archaeological contexts is crucial to understanding ancient civilizations, including the organization of their societies and economies. This study focuses on the interdisciplinary application of mathematical logical data analysis to Egyptology, particularly examining food production in the Workmen’s Village of Amarna. The introduction provides historical context about Amarna, founded by Pharaoh Akhenaten, and outlines the settlement structure and excavations of the Workmen’s Village. The research utilizes archaeobotanical and archaeological data, along with digital humanities tools, to identify activity areas related to food production. The findings reveal spatial patterns in the distribution of tools such as mortars, pestles, and ovens, providing insights into the self-sufficiency and daily life of the villagers. Logical data analysis helps in finding rules and patterns in a dataset which are not visible otherwise, predicting the distribution of unexcavated areas and thus in this case enhancing our understanding of ancient Egyptian food production practices in state- planned settlements. Y1 - 2025 U6 - https://doi.org/10.1515/itit-2024-0088 VL - 66 IS - 6 SP - 256 EP - 268 PB - de Gruyter ER - TY - JOUR A1 - Vu, Thi Huong A1 - Xu, Hong-Kun A1 - Nguyen, Dong Yen T1 - Stability analysis of split equality and split feasibility problems JF - Journal of Global Optimization N2 - In this paper, for the first time in the literature, we study the stability of solutions of two classes of feasibility (i.e., split equality and split feasibility) problems by set-valued and variational analysis techniques. Our idea is to equivalently reformulate the feasibility problems as parametric generalized equations to which set-valued and variational analysis techniques apply. Sufficient conditions, as well as necessary conditions, for the Lipschitz-likeness of the involved solution maps are proved by exploiting special structures of the problems and by using an advanced result of B.S. Mordukhovich [J. Global Optim. 28, 347–362 (2004)]. These conditions stand on a solid interaction among all the input data by means of their dual counterparts, which are transposes of matrices and regular/limiting normal cones to sets. Several examples are presented to illustrate how the obtained results work in practice and also show that the assumption on the existence of a nonzero solution used in the necessity conditions cannot be lifted. Y1 - 2025 U6 - https://doi.org/10.1007/s10898-025-01469-6 SN - 0925-5001 VL - 92 SP - 411 EP - 429 PB - Springer Science and Business Media LLC ER - TY - CHAP A1 - Schade, Johannes A1 - von Tycowicz, Christoph A1 - Hanik, Martin T1 - Bi-invariant Geodesic Regression with Data from the Osteoarthritis Initiative T2 - Information Processing in Medical Imaging N2 - Many phenomena are naturally characterized by measuring continuous transformations such as shape changes in medicine or articulated systems in robotics. Modeling the variability in such datasets requires performing statistics on Lie groups, that is, manifolds carrying an additional group structure. As the Lie group captures the symmetries in the data, it is essential from a theoretical and practical perspective to ask for statistical methods that respect these symmetries; this way they are insensitive to confounding effects, e.g., due to the choice of reference coordinate systems. In this work, we investigate geodesic regression---a generalization of linear regression originally derived for Riemannian manifolds. While Lie groups can be endowed with Riemannian metrics, these are generally incompatible with the group structure. We develop a non-metric estimator using an affine connection setting. It captures geodesic relationships respecting the symmetries given by left and right translations. For its computation, we propose an efficient fixed point algorithm requiring simple differential expressions that can be calculated through automatic differentiation. We perform experiments on a synthetic example and evaluate our method on an open-access, clinical dataset studying knee joint configurations under the progression of osteoarthritis. Y1 - 2025 U6 - https://doi.org/10.1007/978-3-031-96628-6_4 SP - 49 EP - 63 PB - Springer CY - Lecture Notes in Computer Science ER - TY - CHAP A1 - Martínez-Rubio, David A1 - Roux, Christophe A1 - Criscitiello, Christopher A1 - Pokutta, Sebastian T1 - Accelerated Methods for Riemannian Min-Max Optimization Ensuring Bounded Geometric Penalties T2 - Proceedings of The 28th International Conference on Artificial Intelligence and Statistics Y1 - 2025 UR - https://raw.githubusercontent.com/mlresearch/v258/main/assets/martinez-rubio25a/martinez-rubio25a.pdf VL - 258 SP - 280 EP - 288 ER - TY - JOUR A1 - Göbel, Fritz A1 - Huynh, Ngoc Mai Monica A1 - Chegini, Fatemeh A1 - Pavarino, Luca A1 - Weiser, Martin A1 - Scacchi, Simone A1 - Anzt, Hartwig T1 - A BDDC Preconditioner for the Cardiac EMI Model in three Dimensions JF - SIAM J. Sci. Comput. N2 - We analyze a Balancing Domain Decomposition by Constraints (BDDC) preconditioner for the solution of three dimensional composite Discontinuous Galerkin discretizations of reaction-diffusion systems of ordinary and partial differential equations arising in cardiac cell-by-cell models like the Extracellular space, Membrane and Intracellular space (EMI) Model. These microscopic models are essential for the understanding of events in aging and structurally diseased hearts which macroscopic models relying on homogenized descriptions of the cardiac tissue, like Monodomain and Bidomain models, fail to adequately represent. The modeling of each individual cardiac cell results in discontinuous global solutions across cell boundaries, requiring the careful construction of dual and primal spaces for the BDDC preconditioner. We provide a scalable condition number bound for the precondition operator and validate the theoretical results with extensive numerical experiments. Y1 - 2025 ER - TY - GEN A1 - Lindner, Niels T1 - A Multi-Commodity Flow Heuristic for Integrated Periodic Timetabling for Railway Construction Sites N2 - Rescheduling a railway system comprises many aspects, such as line planning, timetabling, track allocation, and vehicle scheduling. For periodic timetables, these features can be integrated into a single mixed-integer program extending the Periodic Event Scheduling Problem (PESP) with a routing component. We develop a multi-commodity-flow-based heuristic that allows to compute better solutions faster than a black-box MIP approach on real construction site scenarios on the S-Bahn Berlin network. T3 - ZIB-Report - 25-02 KW - Railway Timetabling KW - Periodic Timetabling KW - Rescheduling KW - Railway Track Allocation Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-99449 SN - 1438-0064 ER - TY - CHAP A1 - Sadiku, Shpresim A1 - Wagner, Moritz A1 - Pokutta, Sebastian T1 - GSE: Group-wise sparse and explainable adversarial attacks T2 - 13th International Conference on Learning Representations (ICLR 2025) Y1 - 2025 UR - https://openreview.net/pdf?id=d54fIsAbff ER - TY - GEN A1 - Ragyanszki, Anita A1 - Ji, Hongchen A1 - Fournier, Rene T1 - Understanding the Origins of Life – A Machine learning approach to estimate reaction mechanisms of biotic precursors T2 - SIMPLAIX N2 - Understanding the Origins of Life - A Machine learning approach to estimate reaction mechanisms of biotic precursors. Life as we know it is the result of billions of years of evolution; however, understanding how the very first organisms came into existence is a challenge that has yet to be solved. One theory states that components of these molecules may have formed in the interstellar medium (ISM) and been transported to Earth. The ISM, with its specific conditions, allows for molecular stability and the formation of biotic precursors that would otherwise be unlikely in Earth's prebiotic conditions. Understanding how these molecules formed in the ISM may be the key to determining how life began. The goal of this research is to develop a model for solving astrobiophysical problems by studying the formation mechanisms of biomolecules found in the ISM. Although such pathways have been studied individually, there has not yet been a comprehensive method to understand the complete reactions mechanisms. Several QM methods are available for finding transition states (TS) and energy barriers (E) of chemical reactions but are time-consuming and can hardly be applied to more complex systems. Our interest is to develop a machine learning approach to approximate TS, and E, requiring as input only estimates of geometry and energies of reactants and products. Y1 - 2024 ER - TY - GEN A1 - Ragyanszki, Anita A1 - Ji, Hongchen A1 - Fournier, Rene T1 - Understanding the Origins of Life - A Machine learning approach to estimate reaction mechanisms of biotic precursors T2 - Perspectives and challenges of future HPC installations for atomistic and molecular simulations N2 - Life as we know it is the result of billions of years of evolution; yet, understanding how the very first organisms came into existence is a challenge that has yet to be solved. One theory states that components of the first biotic molecules may not have formed on Earth. Rather, they may have initially formed in the interstellar medium (ISM) and been transported to Earth, as supported by recorded instances of organic molecules detected in space. The ISM, with its low temperatures and specific collision processes, allows for molecular stability and the formation of biotic precursors that would otherwise be unlikely in Earth's prebiotic conditions. Understanding how these molecules formed in the ISM may be the key to determining how life began. The goal of this research is to develop a new model for solving astrobiophysical problems by studying the formation mechanisms of biomolecules found in the ISM. Although such pathways have been studied individually, there has not yet been a comprehensive method to understand all the formation reactions that can occur in ISM. Several quantum chemical and numerical methods are available for finding transition states (TS) and energy barriers (E) of chemical reactions but are time-consuming and can hardly be applied to systems with more than a few atoms. Our main interest is to develop a a machine learning approach to approximate TS, and E, requiring as input only estimates of geometry and energies of reactants and products. Using a complete dataset 300 reaction features are computed, and an estimate of E is obtained by fitting a Kernel Ridge Regression (KRR) model with Laplacian kernel, and a fully connected Artificial Neural Network (ANN) to estimate reaction energy barriers. Y1 - 2024 ER - TY - JOUR A1 - Ji, Hongchen A1 - Ragyanszki, Anita A1 - Fournier, Rene T1 - A Machine Learning and Quantum Chemistry Approach for Identifying Prebiotic Molecules in the Interstellar Medium JF - Physical Chemistry Chemical Physics N2 - The discovery of molecules in the interstellar medium (ISM) plays a key role in understanding prebiotic chemistry. Relatively few (∼250) molecules have been confirmed in the ISM, and detecting additional species is crucial for expanding our knowledge of astrochemical processes. We present a strategy for predicting possible prebiotic molecules in the ISM that combines machine learning and high-accuracy quantum chemistry calculations. Using a reaction dataset of over 153,000 possible combinations of known interstellar molecules, we applied a machine learning model to estimate reaction energy barriers and identify those with low or zero barriers that are most likely to occur in the ISM. From this screening process, 24 molecules were identified, five of which have already been observed in interstellar space. For the remaining 19 molecules, we conducted density functional theory (DFT) and coupled cluster theory calculations to determine the most stable conformers, spectroscopic parameters, and predict their detectability through spectroscopy. We present data to guide future observational searches for new interstellar species, contributing to the ongoing exploration of complex organic molecules in space and their potential role in prebiotic chemistry. Y1 - 2024 ER - TY - JOUR A1 - Ji, Hongchen A1 - Anita, Ragyanszki A1 - Fournier, Rene T1 - Computational Study of the Reactions of CH2 with HCNO and HNCO JF - Canadian Journal of Chemistry N2 - We present a computational approach for screening reaction mechanisms with machine learning estimates of energy barriers. A comprehensive screening of thousands of reactions identified the CH2 reactions with HCNO and HNCO as possible sources of relatively complex organic molecules in space. We report detailed reaction mechanisms, including TS, intermediate, and product energies, calculated with density functional theory and coupled cluster theory. Singlet CH2, located 9 kcal/mol above the triplet ground state, reacts with HCNO or HNCO without a barrier, producing four prod11 ucts: CH2NCHO, N-methyleneformamide, the thermodynamically favored product; NHCHCHO, imine acetaldehyde; NHCHOCH; and (CH2OC)NH, oxiran-2-ylazanide. The lowest energy pathway for CH2 + HCNO, involving a triplet-to-singlet crossing, has a barrier of 8 kcal/mol and leads to N -methyleneformamide, imine acetaldehyde, and NHCHOCH. The reaction of triplet CH2 with HNCO has a lowest energy pathway with a barrier of 11 kcal/mol, yielding CH2(CO)NH. Y1 - 2025 U6 - https://doi.org/10.1139/cjc-2024-0203 VL - 103 IS - 7 SP - 386 EP - 395 ER - TY - JOUR A1 - Euler, Ricardo A1 - Maristany de las Casas, Pedro A1 - Borndörfer, Ralf T1 - Logic-Constrained Shortest Paths for Flight Planning N2 - The Logic-Constrained Shortest Path Problem (LCSP) combines a one-to-one shortest path problem with satisfiability constraints imposed on the routing graph. This setting arises in flight planning, where air traffic control (ATC) authorities are enforcing a set of traffic flow restrictions (TFRs) on aircraft routes in order to increase safety and throughput. We propose a new branch and bound-based algorithm for the LCSP. The resulting algorithm has three main degrees of freedom: the node selection rule, the branching rule and the conflict. While node selection and branching rules have been long studied in the MIP and SAT communities, most of them cannot be applied out of the box for the LCSP. We review the existing literature and develop tailored variants of the most prominent rules. The conflict, the set of variables to which the branching rule is applied, is unique to the LCSP. We analyze its theoretical impact on the B&B algorithm. In the second part of the paper, we show how to model the Flight Planning Problem with TFRs as an LCSP and solve it using the branch and bound algorithm. We demonstrate the algorithm’s efficiency on a dataset consisting of a global flight graph and a set of around 20000 real TFRs obtained from our industry partner Lufthansa Systems GmbH. We make this dataset publicly available. Finally, we conduct an empirical in-depth analysis of node selection rules, branching rules and conflicts. Carefully choosing an appropriate combination yields an improvement of an order of magnitude compared to an uninformed choice. Y1 - 2024 ER - TY - CHAP A1 - Lößer, Ansgar A1 - Witzke, Joel A1 - Schintke, Florian A1 - Scheuermann, Björn T1 - BottleMod: Modeling Data Flows and Tasks for Fast Bottleneck Analysis T2 - Proceedings of the 16th ACM/SPEC International Conference on Performance Engineering (ICPE 2025) Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?https://doi.org/10.1145/3676151.3719382 SP - 11 EP - 18 PB - Association for Computing Machinery ER - TY - JOUR A1 - del Razo, Mauricio A1 - Kostré, Margarita T1 - Open reaction-diffusion systems: bridging probabilistic theory and simulations across scales JF - Journal of Physics A: Mathematical and Theoretical N2 - Reaction-diffusion processes are the foundational model for a diverse range of complex systems, ranging from biochemical reactions to social agent-based phenomena. The underlying dynamics of these systems occur at the individual particle/agent level, and in realistic applications, they often display interaction with their environment through energy or material exchange with a reservoir. This requires intricate mathematical considerations, especially in the case of material exchange since the varying number of particles/agents results in ``on-the-fly'' modification of the system dimension. In this work, we first overview the probabilistic description of reaction-diffusion processes at the particle level, which readily handles varying number of particles. We then extend this model to consistently incorporate interactions with macroscopic material reservoirs. Based on the resulting expressions, we bridge the probabilistic description with macroscopic concentration-based descriptions for linear and nonlinear reaction-diffusion systems, as well as for an archetypal open reaction-diffusion system. Using these mathematical bridges across scales, we finally develop numerical schemes for open reaction-diffusion systems, which we implement in two illustrative examples. This work establishes a methodological workflow to bridge particle-based probabilistic descriptions with macroscopic concentration-based descriptions of reaction-diffusion in open settings, laying the foundations for a multiscale theoretical framework upon which to construct theory and simulation schemes that are consistent across scales. Y1 - 2025 U6 - https://doi.org/10.1088/1751-8121/adc520 VL - 58 IS - 14 ER - TY - JOUR A1 - Jain, Toshit A1 - Singh, Upkar A1 - Singh, Varun A1 - Boda, Vijay Kumar A1 - Hotz, Ingrid A1 - Vadhiyar, Sathish S. A1 - Vinayachandran, P. N. A1 - Natarajan, Vijay T1 - A Scalable System for Visual Analysis of Ocean Data JF - Computer Graphics Forum Y1 - 2025 U6 - https://doi.org/10.1111/cgf.15279 VL - 44 IS - 1 SP - e15279 ER - TY - JOUR A1 - Becks, Henrik A1 - Lippold, Lukas A1 - Winkler, Paul A1 - Rohrer, Maximilian A1 - Leusmann, Thorsten A1 - Anton, David A1 - Sprenger, Bjarne A1 - Kähler, Philipp A1 - Rudenko, Iryna A1 - Andrés Arcones, Daniel A1 - Koutsourelakis, Phaedon-Stelios A1 - Unger, Jörg F. A1 - Weiser, Martin A1 - Petryna, Yuri A1 - Schnellenbach-Held, Martina A1 - Lowke, Dirk A1 - Wessels, Henning A1 - Lenzen, Armin A1 - Zabel, Volkmar A1 - Könke, Carsten A1 - Claßen, Martin A1 - Hegger, Josef T1 - Neuartige Konzepte für die Zustandsüberwachung und -analyse von Brückenbauwerken – Einblicke in das Forschungsvorhaben SPP100+ JF - Bauingenieur N2 - Die Brückeninfrastruktur in Deutschland und Europa steht aufgrund steigender Verkehrslasten und alternder Bauwerke vor erheblichen Herausforderungen. Das DFG-Schwerpunktprogramm 2388 „Hundert plus – Verlängerung der Lebensdauer komplexer Baustrukturen durch intelligente Digitalisierung“ (SPP100+) strebt an, durch digitale Innovationen und prädiktive Instandhaltungsstrategien die Nutzungsdauer bestehender Brückenbauwerke zu verlängern. Der vorliegende Beitrag fokussiert sich auf das SPP100+ zugehörige Cluster „Monitoring und Simulation“, das sieben Teilprojekte umfasst. Die Projekte entwickeln fortschrittliche Methoden zur Überwachung und Zustandsbewertung von Brücken mittels Digitaler Zwillinge, hochauflösender Sensortechnik und numerischer Simulationen. Innovative Ansätze wie nichtlineare Modellanpassungen, stochastische Methoden und künstliche Intelligenz ermöglichen eine präzise und frühzeitige Identifizierung potenzieller Schäden. Die Kombination aus kontinuierlichem Bauwerksmonitoring und effizienter Datenauswertung ist entscheidend für die langfristige Sicherheit und Langlebigkeit bestehender Brücken und trägt darüber hinaus zur Ressourcenschonung bei. N2 - Bridges in Germany and across Europe face significant challenges due to increasing traffic loads and aging structures. The DFG Priority Programme 2388 “Hundred Plus – Extending the Lifetime of Complex Engineering Structures through Intelligent Digitalization” (SPP100+) aims to extend the lifespan of existing bridge structures through digital innovations and predictive maintenance strategies. This paper focuses on the SPP100+ affiliated cluster “Monitoring and Simulation,” which encompasses seven sub-projects. These projects develop advanced methods for monitoring and assessing the condition of bridge structures using digital twins, high-resolution sensor technology, and numerical simulations. Innovative approaches such as nonlinear model adjustments, stochastic methods, and artificial intelligence facilitate precise and early identification of potential damages. The combination of continuous structural monitoring and efficient data evaluation is crucial for the long-term reliability and durability of existing bridges and contributes to resource conservation. T2 - Novel Concepts for the Condition Monitoring and Analysis of Bridge Structures – Insights into the SPP100+ Research Project Y1 - 2024 U6 - https://doi.org/10.37544/0005-6650-2024-10-63 VL - 99 IS - 10 SP - 327 EP - 338 ER - TY - CHAP A1 - Siqueira Rodrigues, Lucas A1 - Nyakatura, John A1 - Zachow, Stefan A1 - Israel, Johann Habakuk A1 - Kosch, Thomas T1 - Evaluating Visuohaptic Integration on Memory Retention of Morphological Tomographic Images T2 - The 19th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and its Applications in Industry N2 - Scientific visualization and tomographic imaging techniques have created unprecedented possibilities for non-destructive analyses of digital specimens in morphology. However, practitioners encounter difficulties retaining critical information from complex tomographic volumes in their workflows. In light of this challenge, we investigated the effectiveness of visuohaptic integration in enhancing memory retention of morphological data. In a within-subjects user study (N=18), participants completed a delayed match-to-sample task, where we compared error rates and response times across visual and visuohaptic sensory modality conditions. Our results indicate that visuohaptic encoding improves the retention of tomographic images, producing significantly reduced error rates and faster response times than its unimodal visual counterpart. Our findings suggest that integrating haptics into scientific visualization interfaces may support professionals in fields such as morphology, where accurate retention of complex spatial data is essential for efficient analysis and decision-making within virtual environments. Y1 - 2024 U6 - https://doi.org/10.1145/3703619.3706055 SP - 1 EP - 10 PB - ACM CY - New York, NY, USA ER - TY - JOUR A1 - Caruso, Fabio A1 - Sentef, Michael A1 - Attaccalite, Claudio A1 - Bonitz, Michael A1 - Draxl, Claudia A1 - De Giovannini, Umberto A1 - Eckstein, Martin A1 - Ernstorfer, Ralph A1 - Fechner, Michael A1 - Grüning, Myrta A1 - Hübener, Hannes A1 - Joost, Jan-Philip A1 - Juraschek, Dominik A1 - Karrasch, Christoph A1 - Marvin Kennes, Dante A1 - Latini, Simone A1 - Lu, I-Te A1 - Neufeld, Ofer A1 - Perfetto, Enrico A1 - Rettig, Laurenz A1 - Rodrigues Pelá, Ronaldo A1 - Rubio, Angel A1 - Rudzinski, Joseph A1 - Ruggenthaler, Michael A1 - Sangalli, Davide A1 - Schüler, Michael A1 - Shallcross, Samuel A1 - Sharma, Sangeeta A1 - Stefanucci, Gianluca A1 - Werner, Philipp T1 - The 2025 Roadmap to Ultrafast Dynamics: Frontiers of Theoretical and Computational Modelling JF - J. Phys. Mater. Y1 - 2026 U6 - https://doi.org/10.1088/2515-7639/ae1165 VL - 9 IS - 1 ER - TY - GEN A1 - Pedersen, Jaap A1 - Lindner, Niels A1 - Rehfeldt, Daniel A1 - Koch, Thorsten T1 - Integrated Wind Farm Design: Optimizing Turbine Placement and Cable Routing with Wake Effects N2 - An accelerated deployment of renewable energy sources is crucial for a successful transformation of the current energy system, with wind energy playing a key role in this transition. This study addresses the integrated wind farm layout and cable routing problem, a challenging nonlinear optimization problem. We model this problem as an extended version of the Quota Steiner Tree Problem (QSTP), optimizing turbine placement and network connectivity simultaneously to meet specified expansion targets. Our proposed approach accounts for the wake effect - a region of reduced wind speed induced by each installed turbine - and enforces minimum spacing between turbines. We introduce an exact solution framework in terms of the novel Quota Steiner Tree Problem with interference (QSTPI). By leveraging an interference-based splitting strategy, we develop an advanced solver capable of tackling large-scale problem instances. The presented approach outperforms generic state-of-the-art mixed integer programming solvers on our dataset by up to two orders of magnitude. Moreover, we demonstrate that our integrated method significantly reduces the costs in contrast to a sequential approach. Thus, we provide a planning tool that enhances existing planning methodologies for supporting a faster and cost-efficient expansion of wind energy. T3 - ZIB-Report - 25-01 Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-99218 SN - 1438-0064 ER - TY - JOUR A1 - Regényi, Enikő A1 - Mashreghi, Mir-Farzin A1 - Schütte, Christof A1 - Sunkara, Vikram T1 - Exploring transcription modalities from bimodal, single-cell RNA sequencing data JF - NAR Genomics and Bioinformatics N2 - Abstract There is a growing interest in generating bimodal, single-cell RNA sequencing (RNA-seq) data for studying biological pathways. These data are predominantly utilized in understanding phenotypic trajectories using RNA velocities; however, the shape information encoded in the two-dimensional resolution of such data is not yet exploited. In this paper, we present an elliptical parametrization of two-dimensional RNA-seq data, from which we derived statistics that reveal four different modalities. These modalities can be interpreted as manifestations of the changes in the rates of splicing, transcription or degradation. We performed our analysis on a cell cycle and a colorectal cancer dataset. In both datasets, we found genes that are not picked up by differential gene expression analysis (DGEA), and are consequently unnoticed, yet visibly delineate phenotypes. This indicates that, in addition to DGEA, searching for genes that exhibit the discovered modalities could aid recovering genes that set phenotypes apart. For communities studying biomarkers and cellular phenotyping, the modalities present in bimodal RNA-seq data broaden the search space of genes, and furthermore, allow for incorporating cellular RNA processing into regulatory analyses. Y1 - 2024 U6 - https://doi.org/10.1093/nargab/lqae179 SN - 2631-9268 VL - 6 IS - 4 PB - Oxford University Press (OUP) ER - TY - JOUR A1 - Andrés Arcones, Daniel A1 - Weiser, Martin A1 - Koutsourelakis, Phaedon-Stelios A1 - Unger, Jörg F. T1 - Bias Identification Approaches for Model Updating of Simulation-based Digital Twins of Bridges JF - Structural Health Monitoring in the Light of Climate Impact and Data Science. Research and Review Journal of Nondestructive Testing N2 - Simulation-based digital twins of bridges have the potential not only to serve as monitoring devices of the current state of the structure but also to generate new knowledge through physical predictions that allow for better-informed decisionmaking. For an accurate representation of the bridge, the underlying models must be tuned to reproduce the real system. Nevertheless, the necessary assumptions and simplifications in these models irremediably introduce discrepancies between measurements and model response. We will show that quantifying the extent of the uncertainties introduced through the models that lead to such discrepancies provides a better understanding of the real system, enhances the model updating process, and creates more robust and trustworthy digital twins. The inclusion of an explicit bias term will be applied to a representative demonstrator case based on the thermal response of the Nibelungenbrücke of Worms. The findings from this work are englobed in the initiative SPP 100+, whose main aim is the extension of the service life of structures, especially through the implementation of digital twins. Y1 - 2024 U6 - https://doi.org/10.58286/30524 VL - 2 IS - 2 ER - TY - JOUR A1 - Harth, Philipp A1 - Udvary, Daniel A1 - Boelts, Jan A1 - Baum, Daniel A1 - Macke, Jakob H. A1 - Hege, Hans-Christian A1 - Oberlaender, Marcel T1 - Dissecting origins of wiring specificity in dense cortical connectomes JF - bioRxiv N2 - Wiring specificity in the cortex is observed across scales from the subcellular to the network level. It describes the deviations of connectivity patterns from those expected in randomly connected networks. Understanding the origins of wiring specificity in neural networks remains difficult as a variety of generative mechanisms could have contributed to the observed connectome. To take a step forward, we propose a generative modeling framework that operates directly on dense connectome data as provided by saturated reconstructions of neural tissue. The computational framework allows testing different assumptions of synaptic specificity while accounting for anatomical constraints posed by neuron morphology, which is a known confounding source of wiring specificity. We evaluated the framework on dense reconstructions of the mouse visual and the human temporal cortex. Our template model incorporates assumptions of synaptic specificity based on cell type, single-cell identity, and subcellular compartment. Combinations of these assumptions were sufficient to model various connectivity patterns that are indicative of wiring specificity. Moreover, the identified synaptic specificity parameters showed interesting similarities between both datasets, motivating further analysis of wiring specificity across species. Y1 - 2024 U6 - https://doi.org/10.1101/2024.12.14.628490 ER - TY - CHAP A1 - Klenert, Nicolas A1 - Schwoerer, Finn A1 - Hajarolasvadi, Noushin A1 - Bournez, Siloé A1 - Arlt, Tobias A1 - Mahnke, Heinz-Eberhard A1 - Lepper, Verena A1 - Baum, Daniel T1 - Improving the Identification of Layers in 3D Images of Ancient Papyrus using Artificial Neural Networks T2 - 2025 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW), Tucson, AZ, USA N2 - The process of digitally unfolding ancient documents, such as folded papyrus packages, from 3D image data aims to be a non-invasive means to make previously hidden writing visible without risking to damage the precious documents. One of the main tasks necessary to digitally unfold a document is the geometric reconstruction of the writing substrate, which is a prerequisite for its subsequent unfolding. All current reconstruction methods require the existence of an interspace between different layers of the document to ensure a correct topology. Layers that appear merged together in the 3D image often result in wrong connections between layers and thus also in a wrong topology of the reconstructed geometry, which hinders the successful unfolding. Here, we propose to use a neural network to facilitate the discrimination of the layers. Using papyrus documents as an example of a particularly difficult writing material, we show that this significantly reduces the number of wrong connections and improves the overall identification of the layers. This in turn enables fully automatic digital unfolding of large areas of highly complex papyrus packages. Utilizing explainable AI (XAI) further allows us to explore the results of the applied neural network. Y1 - 2025 U6 - https://doi.org/10.1109/WACVW65960.2025.00143 SP - 1204 EP - 1212 ER - TY - GEN A1 - Binkowski, Felix A1 - Betz, Fridtjof A1 - Hammerschmidt, Martin A1 - Zschiedrich, Lin A1 - Burger, Sven T1 - Source code and simulation results: Resonance modes in microstructured photonic waveguides - Efficient and accurate computation based on AAA rational approximation T2 - Zenodo Y1 - 2024 U6 - https://doi.org/10.5281/zenodo.14202408 SP - doi: 10.5281/zenodo.14202408 ER - TY - JOUR A1 - Binkowski, Felix A1 - Betz, Fridtjof A1 - Hammerschmidt, Martin A1 - Zschiedrich, Lin A1 - Burger, Sven T1 - Resonance modes in microstructured photonic waveguides: Efficient and accurate computation based on AAA rational approximation JF - Nanophotonics Y1 - 2025 U6 - https://doi.org/10.1515/nanoph-2024-0755 VL - 14 SP - 1665 ER - TY - JOUR A1 - Clausecker, Robert A1 - Lemire, Daniel A1 - Schintke, Florian T1 - Faster Positional-Population Counts for AVX2, AVX-512, and ASIMD JF - CoRR Y1 - 2024 U6 - https://doi.org/10.48550/arXiv.2412.16370 VL - abs/2412.16370 SP - 1 EP - 23 ER -