@misc{KOBVHrsg2022, author = {KOBV (Hrsg.),}, title = {KOBV-Sondernewsletter zum 25-j{\"a}hrigen Jubil{\"a}um}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-86379}, year = {2022}, abstract = {Der Kooperative Bibliotheksverbund Berlin-Brandenburg wird heute 25 Jahre alt. Seit dem 1. April 1997 entwickelt der KOBV neue Dienstleistungen f{\"u}r Nutzende und Bibliotheken, baut Informationsinfrastrukturen in Berlin und Brandenburg aus, vernetzt Bibliotheken aus der Region und informiert {\"u}ber aktuelle Themen. Im Sondernewsletter geben uns aktuelle und ehemalige KOBV-Mitarbeitende/Mitglieder Antworten auf Fragen zur Entstehung und Weiterentwicklung des Verbundes. Lesen und feiern Sie mit uns zusammen!}, language = {de} } @misc{OPUS4-8559, title = {Annual Report 2019}, volume = {2019}, organization = {Konrad-Zuse-Zentrum f{\"u}r Informationstechnik Berlin}, issn = {0934-5892}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-85594}, pages = {98}, year = {2022}, language = {en} } @misc{OPUS4-8560, title = {Annual Report 2020}, volume = {2020}, organization = {Konrad-Zuse-Zentrum f{\"u}r Informationstechnik Berlin}, issn = {0934-5892}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-85609}, pages = {90}, year = {2022}, language = {en} } @misc{OPUS4-8753, title = {Annual Report 2021}, volume = {2021}, organization = {Konrad-Zuse-Zentrum f{\"u}r Informationstechnik Berlin}, issn = {0934-5892}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-87537}, pages = {104}, year = {2022}, language = {en} } @article{BerioBayleBaumetal.2022, author = {Berio, Fidji and Bayle, Yann and Baum, Daniel and Goudemand, Nicolas and Debiais-Thibaud, M{\´e}lanie}, title = {Hide and seek shark teeth in Random Forests: Machine learning applied to Scyliorhinus canicula populations}, journal = {PeerJ - Aquatic Biology}, doi = {10.7717/peerj.13575}, pages = {10:e13575}, year = {2022}, abstract = {Shark populations that are distributed alongside a latitudinal gradient often display body size differences at sexual maturity and vicariance patterns related to their number of tooth files. Previous works have demonstrated that Scyliorhinus canicula exhibits distinct genetic structures, life history traits, and body size differences between populations inhabiting the North Atlantic Ocean and the Mediterranean Sea. In this work, we sample more than 3,000 S. canicula teeth from 56 specimens and provide and use a dataset containing their shape coordinates. We investigate tooth shape and form differences between a Mediterranean and an Atlantic S. canicula population using two approaches. Classification results show that the classical geometric morphometric framework is outperformed by an original Random Forests-based framework. Visually, both S. canicula populations share similar ontogenetic trends and timing of gynandric heterodonty emergence but the Atlantic population has bigger, blunter teeth, and less numerous accessory cusps than the Mediterranean population. According to the models, the populations are best differentiated based on their lateral tooth edges, which bear accessory cusps, and the tooth centroid sizes significantly improve classification performances. The differences observed are discussed in light of dietary and behavioural habits of the populations considered. The method proposed in this study could be further adapted to complement DNA analyses to identify shark species or populations based on tooth morphologies. This process would be of particular interest for fisheries management and identification of shark fossils.}, language = {en} } @misc{BerioBayleAgretetal.2022, author = {Berio, Fidji and Bayle, Yann and Agret, Sylvie and Baum, Daniel and Goudemand, Nicolas and Debiais-Thibaud, M{\´e}lanie}, title = {3D models related to the publication: Hide and seek shark teeth in Random Forests: Machine learning applied to Scyliorhinus canicula}, journal = {MorphoMuseuM}, doi = {10.18563/journal.m3.164}, year = {2022}, abstract = {The present dataset contains the 3D models analyzed in Berio, F., Bayle, Y., Baum, D., Goudemand, N., and Debiais-Thibaud, M. 2022. Hide and seek shark teeth in Random Forests: Machine learning applied to Scyliorhinus canicula. It contains the head surfaces of 56 North Atlantic and Mediterranean small-spotted catsharks Scyliorhinus canicula, from which tooth surfaces were further extracted to perform geometric morphometrics and machine learning.}, language = {en} } @article{RodriguesPelaDraxl2022, author = {Rodrigues Pel{\´a}, Ronaldo and Draxl, Claudia}, title = {Ehrenfest dynamics implemented in the all-electron package exciting}, volume = {4}, journal = {Electron. Struct.}, doi = {10.1088/2516-1075/ac7afc}, pages = {037001}, year = {2022}, abstract = {Ehrenfest dynamics combined with real-time time-dependent density functional theory has proven to be a reliable tool to study non-adiabatic molecular dynamics with a reasonable computational cost. Among other possibilities, it allows for assessing in real time electronic excitations generated by ultra-fast laser pulses, as e.g., in pump-probe spectroscopy, and their coupling to the nuclear vibrations even beyond the linear regime. In this work, we present its implementation in the all-electron full-potential package exciting. Three cases are presented as examples: diamond and cubic boron nitride (BN) relaxed after an initial lattice distortion, and cubic BN exposed to a laser pulse. Comparison with the Octopus code exhibits good agreement.}, language = {en} } @article{BeronVeraOlascoagaHelfmannetal.2023, author = {Beron-Vera, Francisco Javier and Olascoaga, Maria Josefina and Helfmann, Luzie and Miron, Philippe}, title = {Sampling-Dependent Transition Paths of Iceland-Scotland Overflow Water}, volume = {53}, journal = {Journal of Physical Oceanography}, number = {4}, arxiv = {http://arxiv.org/abs/2208.09499}, doi = {10.1175/JPO-D-22-0172.1}, pages = {1151 -- 1160}, year = {2023}, abstract = {In this note, we apply Transition Path Theory (TPT) from Markov chains to shed light on the problem of Iceland-Scotland Overflow Water (ISOW) equatorward export. A recent analysis of observed trajectories of submerged floats demanded revision of the traditional abyssal circulation theory, which postulates that ISOW should steadily flow along a deep boundary current (DBC) around the subpolar North Atlantic prior to exiting it. The TPT analyses carried out here allow to focus the attention on the portions of flow from the origin of ISOW to the region where ISOW exits the subpolar North Atlantic and suggest that insufficient sampling may be biasing the aforementioned demand. The analyses, appropriately adapted to represent a continuous input of ISOW, are carried out on three time-homogeneous Markov chains modeling the ISOW flow. One is constructed using a high number of simulated trajectories homogeneously covering the flow domain. The other two use much fewer trajectories which heterogeneously cover the domain. The trajectories in the latter two chains are observed trajectories or simulated trajectories subsampled at the observed frequency. While the densely sampled chain supports a well-defined DBC, the more heterogeneously sampled chains do not, irrespective of whether observed or simulated trajectories are used. Studying the sampling sensitivity of the Markov chains, we can give recommendations for enlarging the existing float dataset to improve the significance of conclusions about time-asymptotic aspects of the ISOW circulation.}, language = {en} } @inproceedings{ProdanovVohra2022, author = {Prodanov, Dimiter and Vohra, Sumit Kumar}, title = {Active Segmentation: Differential Geometry meets Machine Learning}, booktitle = {Proceedings of the 23rd International Conference on Computer Systems and Technologies}, doi = {10.1145/3546118.3546154}, pages = {1 -- 6}, year = {2022}, abstract = {Image segmentation is an active area of research for more than 30 years. Traditional image segmentation algorithms are problem-specific and limited in scope. On the other hand, machine learning offers an alternative paradigm where predefined features are combined into different classifiers, providing pixel-level classification and segmentation. However, machine learning only can not address the question as to which features are appropriate for a certain classification problem. This paper presents a project supported in part by the International Neuroinformatics Coordination Facility through the Google Summer of code. The project resulted in an automated image segmentation and classification platform, called Active Segmentation for ImageJ (AS/IJ). The platform integrates a set of filters computing differential geometrical invariants and combines them with machine learning approaches.}, language = {en} } @masterthesis{Wyczisk2016, type = {Bachelor Thesis}, author = {Wyczisk, Christopher}, title = {Portfoliooptimierung mittels mathematischer Optimierung}, year = {2016}, language = {de} } @misc{SchwartzBorndoerferBartz2016, author = {Schwartz, Stephan and Bornd{\"o}rfer, Ralf and Bartz, Gerald}, title = {The Graph Segmentation Problem}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-60750}, year = {2016}, abstract = {We investigate a graph theoretical problem arising in the automatic billing of a network toll. Given a network and a family of user paths, we study the graph segmentation problem (GSP) to cover parts of the user paths by a set of disjoint segments. The GSP is shown to be NP-hard but for special cases it can be solved in polynomial time. We also show that the marginal utility of a segment is bounded. Computational results for real-world instances show that in practice the problem is more amenable than the theoretic bounds suggest.}, language = {en} } @inproceedings{MatuschkeBleyMueller2013, author = {Matuschke, Jannik and Bley, Andreas and M{\"u}ller, Benjamin}, title = {Approximation Algorithms for Facility Location with Capacitated and Length-Bounded Tree Connections}, volume = {Algorithms -- ESA 2013}, editor = {Bodlaender, Hans L. and Italiano, Giuseppe F.}, publisher = {Springer}, doi = {10.1007/978-3-642-40450-4_60}, pages = {707 -- 718}, year = {2013}, abstract = {We consider a generalization of the uncapacitated facility location problem that occurs in planning of optical access networks in telecommunications. Clients are connected to open facilities via depth-bounded trees. The total demand of clients served by a tree must not exceed a given tree capacity. We investigate a framework for combining facility location algorithms with a tree-based clustering approach and derive approximation algorithms for several variants of the problem, using techniques for approximating shallow-light Steiner trees via layer graphs, simultaneous approximation of shortest paths and minimum spanning trees, and greedy coverings.}, language = {en} } @book{OPUS4-5024, title = {MATHEON - Mathematics for Key Technologies}, volume = {1}, editor = {Deuflhard, Peter and Gr{\"o}tschel, Martin and H{\"o}mberg, Dietmar and Horst, Ulrich and Kramer, J{\"u}rg and Mehrmann, Volker and Polthier, Konrad and Schmidt, Frank and Sch{\"u}tte, Christof and Skutella, Martin and Sprekels, J{\"u}rgen}, publisher = {European Mathematical Society}, isbn = {978-3-03719-137-8}, doi = {10.4171/137}, year = {2014}, language = {en} } @misc{PulajRaymondTheis2015, author = {Pulaj, Jonad and Raymond, Annie and Theis, Dirk}, title = {New Conjectures For Union-Closed Families}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-56804}, year = {2015}, abstract = {The Frankl conjecture, also known as the union-closed sets conjecture, states that there exists an element in at least half of the sets of any (non-empty) union-closed family. From an optimization point of view, one could instead prove that 2a is an upper bound to the number of sets in a union-closed family with n elements where each element is in at most a sets, where a and n are non-negative integers. Formulating these problems as integer programs we observe that computed optimal values do not vary with n. We formalize these observations as conjectures, and show that they are not equivalent to the Frankl conjecture while still having wide-reaching implications if proven true. Finally, we partially prove the new conjectures and discuss possible approaches to solve them completely.}, language = {en} } @article{Groetschel2015, author = {Gr{\"o}tschel, Martin}, title = {Die IMU und ihr Sekretariat}, volume = {23}, journal = {Mitteilungen der DMV}, number = {1}, doi = {10.1515/dmvm-2015-0012}, pages = {24 -- 29}, year = {2015}, abstract = {Was macht die International Mathematical Union (IMU) eigentlich, und wozu ist das IMU-Sekretariat da? ...}, language = {de} } @article{CardereraPokuttaSchuetteetal.2025, author = {Carderera, Alejandro and Pokutta, Sebastian and Sch{\"u}tte, Christof and Weiser, Martin}, title = {An efficient first-order conditional gradient algorithm in data-driven sparse identification of nonlinear dynamics to solve sparse recovery problems under noise}, volume = {470}, journal = {Journal of Computational and Applied Mathematics}, doi = {10.1016/j.cam.2025.116675}, year = {2025}, abstract = {Governing equations are essential to the study of nonlinear dynamics, often enabling the prediction of previously unseen behaviors as well as the inclusion into control strategies. The discovery of governing equations from data thus has the potential to transform data-rich fields where well-established dynamical models remain unknown. This work contributes to the recent trend in data-driven sparse identification of nonlinear dynamics of finding the best sparse fit to observational data in a large library of potential nonlinear models. We propose an efficient first-order Conditional Gradient algorithm for solving the underlying optimization problem. In comparison to the most prominent alternative framework, the new framework shows significantly improved performance on several essential issues like sparsity-induction, structure-preservation, noise robustness, and sample efficiency. We demonstrate these advantages on several dynamics from the field of synchronization, particle dynamics, and enzyme chemistry.}, 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{LasbyZimmerPokuttaetal.2025, author = {Lasby, Mike and Zimmer, Max and Pokutta, Sebastian and Schultheis, Erik}, title = {Compressed sparse tiles for memory-efficient unstructured and semi-structured sparsity}, booktitle = {Proceedings of the ICLR Workshop on Sparsity in LLMs}, year = {2025}, 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{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{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} } @inproceedings{VillimNguyenBobiketal.2025, author = {Villim, J{\´a}n and Nguyen, Martin and Bobik, Pavol and Genci, Jan and Gec{\´a}šek, Daniel}, title = {New Version of the COR Simulation Engine}, volume = {501}, booktitle = {Proceedings of 39th International Cosmic Ray Conference — PoS(ICRC2025)}, publisher = {Sissa Medialab}, address = {Trieste, Italy}, doi = {https://doi.org/10.22323/1.501.1377}, year = {2025}, abstract = {The COR simulation engine is a tool devoted to evaluating cosmic ray trajectories in Earth's magnetosphere. It is part of the COR System, available at https://cor.crmodels.org, and it also functions as a standalone command line tool. The former tool was published in 2022. We report the new version of the tool status with improved performance, precision, new functions/features, and refactored code.}, language = {en} } @article{GonnermannMuellerHaaseLeinsetal.2026, author = {Gonnermann-M{\"u}ller, Jana and Haase, Jennifer and Leins, Nicolas and Igel, Moritz and Fackeldey, Konstantin and Pokutta, Sebastian}, title = {FACET: Multi-Agent AI Supporting Teachers in Scaling Differentiated Learning for Diverse Students}, journal = {arXiv}, arxiv = {http://arxiv.org/abs/2601.22788}, doi = {https://arxiv.org/abs/2601.22788}, year = {2026}, abstract = {Classrooms are becoming increasingly heterogeneous, comprising learners with diverse performance and motivation levels, language proficiencies, and learning differences such as dyslexia and ADHD. While teachers recognize the need for differentiated instruction, growing workloads create substantial barriers, making differentiated instruction an ideal that is often unrealized in practice. Current AI educational tools, which promise differentiated materials, are predominantly student-facing and performance-centric, ignoring other aspects that shape learning outcomes. We introduce FACET, a teacher-facing multi-agent framework designed to address these gaps by supporting differentiation that accounts for motivation, performance, and learning differences. Developed with educational stakeholders from the outset, the framework coordinates four specialized agents, including learner simulation, diagnostic assessment, material generation, and evaluation within a teacher-in-the-loop design. School principals (N = 30) shaped system requirements through participatory workshops, while in-service K-12 teachers (N = 70) evaluated material quality. Mixed-methods evaluation demonstrates strong perceived value for inclusive differentiation. Practitioners emphasized both the urgent need arising from classroom heterogeneity and the importance of maintaining pedagogical autonomy as a prerequisite for adoption. We discuss implications for future school deployment and outline partnerships for longitudinal classroom implementation.}, language = {en} } @inproceedings{ScheltenChristgauSchulteetal.2026, author = {Schelten, Niklas and Christgau, Steffen and Schulte, Anton and Schnor, Bettina and Signer, Hannes and Stabernack, Benno}, title = {A Flexible Open-Source Framework for FPGA-based Network-Attached Accelerators using SpinalHDL}, booktitle = {Architecture of Computing Systems - 39th International Conference, ARCS 2026, Mainz, Germany, March 24-26, 2026, Proceedings.}, year = {2026}, abstract = {Domain-specific accelerators are increasingly vital in heterogeneous computing systems, driven by the demand for higher computational capacity and especially energy efficiency. Network-attached FPGAs promise a scalable and flexible alternative to closely coupled FPGAs for integrating accelerators into computing environments. While the advantages of specialized hardware implementations are apparent, traditional hardware development and integration remain time-consuming and complex. We present an open-source framework which combines a hardware shell with supporting software libraries, which enables fast development and deployment of FPGA-based network-attached accelerators. In contrast to traditional approaches using VHDL or Verilog, we leverage generative programming with SpinalHDL, providing a flexible hardware description with multi-level abstractions. This work eases the integration of accelerators into existing network infrastructures and simplifies adaptation to different FPGAs, eliminating complex and lengthy top-level hardware descriptions.}, language = {en} } @article{Zhang2021, author = {Zhang, Wei}, title = {Some new results on relative entropy production, time reversal, and optimal control of time-inhomogeneous diffusion processes}, volume = {62}, journal = {Journal of Mathematical Physics}, number = {4}, arxiv = {http://arxiv.org/abs/2006.11212}, doi = {10.1063/5.0038740}, pages = {26}, year = {2021}, abstract = {This paper studies time-inhomogeneous nonequilibrium diffusion processes, including both Brownian dynamics and Langevin dynamics. We derive upper bounds of the relative entropy production of the time-inhomogeneous process with respect to the transient invariant probability measures. We also study the time reversal of the reverse process in Crooks' fluctuation theorem. We show that the time reversal of the reverse process coincides with the optimally controlled forward process that leads to zero variance importance sampling estimator based on Jarzynski's equality.}, language = {en} } @article{LelievreStoltzZhang2022, author = {Lelievre, Tony and Stoltz, Gabriel and Zhang, Wei}, title = {Multiple projection MCMC algorithms on submanifolds}, journal = {IMA Journal of Numerical Analysis}, arxiv = {http://arxiv.org/abs/2003.09402}, doi = {10.1093/imanum/drac006}, year = {2022}, abstract = {We propose new Markov Chain Monte Carlo algorithms to sample probability distributions on submanifolds, which generalize previous methods by allowing the use of set-valued maps in the proposal step of the MCMC algorithms. The motivation for this generalization is that the numerical solvers used to project proposed moves to the submanifold of interest may find several solutions. We show that the new algorithms indeed sample the target probability measure correctly, thanks to some carefully enforced reversibility property. We demonstrate the interest of the new MCMC algorithms on illustrative numerical examples.}, language = {en} } @article{ZhangLiSchuette2022, author = {Zhang, Wei and Li, Tiejun and Sch{\"u}tte, Christof}, title = {Solving eigenvalue PDEs of metastable diffusion processes using artificial neural networks}, volume = {465}, journal = {Journal of Computational Physics}, arxiv = {http://arxiv.org/abs/2110.14523}, doi = {10.1016/j.jcp.2022.111377}, year = {2022}, abstract = {In this paper, we consider the eigenvalue PDE problem of the infinitesimal generators of metastable diffusion processes. We propose a numerical algorithm based on training artificial neural networks for solving the leading eigenvalues and eigenfunctions of such high-dimensional eigenvalue problem. The algorithm is useful in understanding the dynamical behaviors of metastable processes on large timescales. We demonstrate the capability of our algorithm on a high-dimensional model problem, and on the simple molecular system alanine dipeptide.}, 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{ZhaoZhangLi2024, author = {Zhao, Yue and Zhang, Wei and Li, Tiejun}, title = {EPR-Net: Constructing non-equilibrium potential landscape via a variational force projection formulation}, volume = {11}, journal = {National Science Review}, number = {7}, doi = {10.1093/nsr/nwae052}, year = {2024}, abstract = {We present EPR-Net, a novel and effective deep learning approach that tackles a crucial challenge in biophysics: constructing potential landscapes for high-dimensional non-equilibrium steady-state (NESS) systems. EPR-Net leverages a nice mathematical fact that the desired negative potential gradient is simply the orthogonal projection of the driving force of the underlying dynamics in a weighted inner-product space. Remarkably, our loss function has an intimate connection with the steady entropy production rate (EPR), enabling simultaneous landscape construction and EPR estimation. We introduce an enhanced learning strategy for systems with small noise, and extend our framework to include dimensionality reduction and state-dependent diffusion coefficient case in a unified fashion. Comparative evaluations on benchmark problems demonstrate the superior accuracy, effectiveness, and robustness of EPR-Net compared to existing methods. We apply our approach to challenging biophysical problems, such as an 8D limit cycle and a 52D multi-stability problem, which provide accurate solutions and interesting insights on constructed landscapes. With its versatility and power, EPR-Net offers a promising solution for diverse landscape construction problems in biophysics.}, language = {en} } @article{JiAnitaFournier2025, author = {Ji, Hongchen and Anita, Ragyanszki and Fournier, Rene}, title = {Computational Study of the Reactions of CH2 with HCNO and HNCO}, volume = {103}, journal = {Canadian Journal of Chemistry}, number = {7}, doi = {10.1139/cjc-2024-0203}, pages = {386 -- 395}, year = {2025}, abstract = {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.}, 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{ZhangSchuette2025, author = {Zhang, Wei and Sch{\"u}tte, Christof}, title = {On finding optimal collective variables for complex systems by minimizing the deviation between effective and full dynamics}, volume = {23}, journal = {Multiscale Modeling and Simulation}, number = {2}, arxiv = {http://arxiv.org/abs/2405.02001}, doi = {10.1137/24M1658917}, pages = {924 -- 958}, year = {2025}, abstract = {This paper is concerned with collective variables, or reaction coordinates, that map a discrete-in-time Markov process X_n in R^d to a (much) smaller dimension k≪d. We define the effective dynamics under a given collective variable map ξ as the best Markovian representation of X_n under ξ. The novelty of the paper is that it gives strict criteria for selecting optimal collective variables via the properties of the effective dynamics. In particular, we show that the transition density of the effective dynamics of the optimal collective variable solves a relative entropy minimization problem from certain family of densities to the transition density of X_n. We also show that many transfer operator-based data-driven numerical approaches essentially learn quantities of the effective dynamics. Furthermore, we obtain various error estimates for the effective dynamics in approximating dominant timescales / eigenvalues and transition rates of the original process X_n and how optimal collective variables minimize these errors. Our results contribute to the development of theoretical tools for the understanding of complex dynamical systems, e.g. molecular kinetics, on large timescales. These results shed light on the relations among existing data-driven numerical approaches for identifying good collective variables, and they also motivate the development of new methods.}, 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} } @article{SharmaZhang2021, author = {Sharma, Upanshu and Zhang, Wei}, title = {Non-reversible sampling schemes on submanifolds}, volume = {59}, journal = {SIAM Journal on Numerical Analysis}, number = {6}, arxiv = {http://arxiv.org/abs/2011.02835}, doi = {10.1137/20M1378752}, pages = {2989 -- 3031}, year = {2021}, abstract = {Calculating averages with respect to probability measures on submanifolds is often necessary in various application areas such as molecular dynamics, computational statistical mechanics and Bayesian statistics. In recent years, various numerical schemes have been proposed in the literature to study this problem based on appropriate reversible constrained stochastic dynamics. In this paper we present and analyse a non-reversible generalisation of the projection-based scheme developed by one of the authors [ESAIM: M2AN, 54 (2020), pp. 391-430]. This scheme consists of two steps - starting from a state on the submanifold, we first update the state using a non-reversible stochastic differential equation which takes the state away from the submanifold, and in the second step we project the state back onto the manifold using the long-time limit of a ordinary differential equation. We prove the consistency of this numerical scheme and provide quantitative error estimates for estimators based on finite-time running averages. Furthermore, we present theoretical analysis which shows that this scheme outperforms its reversible counterpart in terms of asymptotic variance. We demonstrate our findings on an illustrative test example.}, language = {en} } @article{LiuZhangSchuetteetal.2025, author = {Liu, Zichen and Zhang, Wei and Sch{\"u}tte, Christof and Li, Tiejun}, title = {Riemannian denoising diffusion probabilistic models}, journal = {Communications in Mathematical Sciences}, arxiv = {http://arxiv.org/abs/2505.04338}, year = {2025}, abstract = {We propose Riemannian Denoising Diffusion Probabilistic Models (RDDPMs) for learning distributions on submanifolds of Euclidean space that are level sets of functions, including most of the manifolds relevant to applications. Existing methods for generative modeling on manifolds rely on substantial geometric information such as geodesic curves or eigenfunctions of the Laplace-Beltrami operator and, as a result, they are limited to manifolds where such information is available. In contrast, our method, built on a projection scheme, can be applied to more general manifolds, as it only requires being able to evaluate the value and the first order derivatives of the function that defines the submanifold. We provide a theoretical analysis of our method in the continuous-time limit, which elucidates the connection between our RDDPMs and score-based generative models on manifolds. The capability of our method is demonstrated on datasets from previous studies and on new datasets sampled from two high-dimensional manifolds, i.e. SO(10) and the configuration space of molecular system alanine dipeptide with fixed dihedral angle.}, language = {en} } @article{LelievrePigeonStoltzetal.2024, author = {Leli{\`e}vre, Tony and Pigeon, Thomas and Stoltz, Gabriel and Zhang, Wei}, title = {Analyzing multimodal probability measures with autoencoders}, volume = {128}, journal = {J. Phys. Chem. B}, number = {11}, doi = {10.1021/acs.jpcb.3c07075}, pages = {2607 -- 2631}, year = {2024}, abstract = {Finding collective variables to describe some important coarse-grained information on physical systems, in particular metastable states, remains a key issue in molecular dynamics. Recently, machine learning techniques have been intensively used to complement and possibly bypass expert knowledge in order to construct collective variables. Our focus here is on neural network approaches based on autoencoders. We study some relevant mathematical properties of the loss function considered for training autoencoders, and provide physical interpretations based on conditional variances and minimum energy paths. We also consider various extensions in order to better describe physical systems, by incorporating more information on transition states at saddle points, and/or allowing for multiple decoders in order to describe several transition paths. Our results are illustrated on toy two dimensional systems and on alanine dipeptide.}, language = {en} } @article{ZhangSchuette2023, author = {Zhang, Wei and Sch{\"u}tte, Christof}, title = {Understanding recent deep-learning techniques for identifying collective variables of molecular dynamics}, volume = {23}, journal = {Proceedings in Applied Mathematics and Mechanics}, number = {4}, doi = {10.1002/pamm.202300189}, year = {2023}, abstract = {High-dimensional metastable molecular dynamics (MD) can often be characterised by a few features of the system, that is, collective variables (CVs). Thanks to the rapid advance in the area of machine learning and deep learning, various deep learning-based CV identification techniques have been developed in recent years, allowing accurate modelling and efficient simulation of complex molecular systems. In this paper, we look at two different categories of deep learning-based approaches for finding CVs, either by computing leading eigenfunctions of transfer operator associated to the underlying dynamics, or by learning an autoencoder via minimisation of reconstruction error. We present a concise overview of the mathematics behind these two approaches and conduct a comparative numerical study of these two approaches on illustrative examples.}, language = {en} } @misc{HartmannRichterSchuetteetal.2017, author = {Hartmann, Carsten and Richter, Lorenz and Sch{\"u}tte, Christof and Zhang, Wei}, title = {Variational characterization of free energy: Theory and algorithms}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-65045}, year = {2017}, abstract = {The article surveys and extends variational formulations of the thermodynamic free energy and discusses their information-theoretic content from the perspective of mathematical statistics. We revisit the well-known Jarzynski equality for nonequilibrium free energy sampling within the framework of importance sampling and Girsanov change-of-measure transformations. The implications of the different variational formulations for designing efficient stochastic optimization and nonequilibrium simulation algorithms for computing free energies are discussed and illustrated.}, 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} } @inproceedings{ScheltenChristgauHutzleretal.2026, author = {Schelten, Niklas and Christgau, Steffen and Hutzler, Merit and Kreowsky, Philipp and De Lucia, Marco and Schnor, Bettina and Signer, Hannes and Spazier, Johannes and Stabernack, Benno and Yahdzhyiev, Serhii}, title = {Using FPGA-based Network-Attached Accelerators for Energy-Efficient AI Training in HPC Datacenters}, booktitle = {2026 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)}, year = {2026}, abstract = {FPGA-based Network-Attached Accelerators offer a disaggregated alternative to closely-coupled FPGAs or GPUs, but their adoption is very limited due to missing hardware/software frameworks. However, the usability and energy-efficiency of FPGAs for HPC use-cases has been demonstrated previously. Yet, the support by HPC infrastructure for those devices is lacking behind other accelerators. This paper addresses this shortcoming and demonstrates a full-stack approach that seamlessly integrates Network-Attached Accelerators in HPC datacenters and allows flexible and scalable usage of FPGAs. The presented work includes the according framework, integration steps and a show-case application from the geoscience domain. We evaluate our approach by comparing the training of a Physics-Informed Neural Network on the NAA against two GPU implementations. The NAA reduces total energy consumption by about 50\% and 17\% compared to the Keras and CUDA implementation, respectively. These results demonstrate that FPGA-based NAAs can be successfully integrated into HPC environments and are a viable path toward more energy-efficient AI training.}, language = {en} } @inproceedings{SunkaraRostamivonTycowiczetal.2026, author = {Sunkara, Vikram and Rostami, Atefe and von Tycowicz, Christoph and Sch{\"u}tte, Christof}, title = {Stop throwing away your Decoder; extract the learnt local coordinate system using Latent-XAI}, booktitle = {The 4th World Conference on Explainable Artificial Intelligence (XAI-2026)}, year = {2026}, language = {en} }