@article{JungNowackaBarisinetal.2023, author = {Jung, Christian and Nowacka, Anna and Barisin, Tin and Meinel, Dietmar and Paetsch, Olaf and Grzesiak, Szymon and Salamon, Michael and Schladitz, Katja and Redenbach, Claudia and Pahn, Matthias}, title = {3d imaging and analysis of cracks in loaded concrete samples. 12th Conference on Industrial Computed Tomography (iCT) 2023, 27 February - 2 March 2023 in F{\"u}rth, Germany}, volume = {28}, journal = {e-Journal of Nondestructive Testing}, number = {3}, doi = {10.58286/27721}, year = {2023}, abstract = {Concrete plays a central role as the standard building material in civil engineering. Experimental characterization of the concrete microstructure and a description of failure mechanisms are important to understand the concrete's mechanical properties. Computed tomography is a powerful source of information as it yields 3d images of concrete specimens. However, complete visual inspection is often infeasible due to very large image sizes. Hence, automatic methods for crack detection and segmentation are needed. A region-growing algorithm and a 3d U-Net showed promising results in a previous study. Cracks in normal concrete and high-performance concrete that were initiated via tensile tests were investigated. Here, the methods are validated on a more diverse set of concrete types and crack characteristics. Adequate adaptions of the methods are necessary to deal with the complex crack structures. The segmentation results are assessed qualitatively and compared to those of a template matching algorithm which is well-established in industry.}, language = {en} } @article{BoltzKurchanLiu2021, author = {Boltz, Horst-Holger and Kurchan, Jorge and Liu, Andrea J.}, title = {Fluctuation distributions of energy minima in complex landscapes}, volume = {3}, journal = {Physical Review Research}, number = {1}, doi = {10.1103/PhysRevResearch.3.013061}, pages = {013061}, year = {2021}, abstract = {We discuss the properties of the distributions of energies of minima obtained by gradient descent in complex energy landscapes. We find strikingly similar phenomenology across several prototypical models. We particularly focus on the distribution of energies of minima in the analytically well-understood p-spin-interaction spin-glass model. We numerically find non-Gaussian distributions that resemble the Tracy-Widom distributions often found in problems of random correlated variables, and nontrivial finite-size scaling. Based on this, we propose a picture of gradient-descent dynamics that highlights the importance of a first-passage process in the eigenvalues of the Hessian. This picture provides a concrete link to problems in which the Tracy-Widom distribution is established. Aspects of this first-passage view of gradient-descent dynamics are generic for nonconvex complex landscapes, rationalizing the commonality that we find across models.}, language = {en} } @article{HoeflingDietrich2020, author = {H{\"o}fling, Felix and Dietrich, Siegfried}, title = {Finite-size corrections for the static structure factor of a liquid slab with open boundaries}, volume = {153}, journal = {The Journal of Chemical Physics}, doi = {10.1063/5.0017923}, pages = {054119}, year = {2020}, abstract = {The presence of a confining boundary can modify the local structure of a liquid markedly. In addition, small samples of finite size are known to exhibit systematic deviations of thermodynamic quantities relative to their bulk values. Here, we consider the static structure factor of a liquid sample in slab geometry with open boundaries at the surfaces, which can be thought of as virtually cutting out the sample from a macroscopically large, homogeneous fluid. This situation is a relevant limit for the interpretation of grazing-incidence diffraction experiments at liquid interfaces and films. We derive an exact, closed expression for the slab structure factor, with the bulk structure factor as the only input. This shows that such free boundary conditions cause significant differences between the two structure factors, in particular, at small wavenumbers. An asymptotic analysis of this result yields the scaling exponent and an accurate, useful approximation of these finite-size corrections. Furthermore, the open boundaries permit the interpretation of the slab as an open system, supporting particle exchange with a reservoir. We relate the slab structure factor to the particle number fluctuations and discuss conditions under which the subvolume of the slab represents a grand canonical ensemble with chemical potential μ and temperature T. Thus, the open slab serves as a test-bed for the small-system thermodynamics in a μT reservoir. We provide a microscopically justified and exact result for the size dependence of the isothermal compressibility. Our findings are corroborated by simulation data for Lennard-Jones liquids at two representative temperatures.}, language = {en} } @article{EbrahimiViandHoeflingKleinetal.2020, author = {Ebrahimi Viand, Roya and H{\"o}fling, Felix and Klein, Rupert and Delle Site, Luigi}, title = {Theory and simulation of open systems out of equilibrium}, volume = {153}, journal = {The Journal of Chemical Physics}, doi = {10.1063/5.0014065}, pages = {101102}, year = {2020}, abstract = {We consider the theoretical model of Bergmann and Lebowitz for open systems out of equilibrium and translate its principles in the adaptive resolution simulation molecular dynamics technique. We simulate Lennard-Jones fluids with open boundaries in a thermal gradient and find excellent agreement of the stationary responses with the results obtained from the simulation of a larger locally forced closed system. The encouraging results pave the way for a computational treatment of open systems far from equilibrium framed in a well-established theoretical model that avoids possible numerical artifacts and physical misinterpretations.}, language = {en} } @article{delRazoDibakSchuetteetal.2021, author = {del Razo, Mauricio J. and Dibak, Manuel and Sch{\"u}tte, Christof and No{\´e}, Frank}, title = {Multiscale molecular kinetics by coupling Markov state models and reaction-diffusion dynamics}, volume = {155}, journal = {The Journal of Chemical Physics}, number = {12}, doi = {10.1063/5.0060314}, year = {2021}, language = {en} } @article{SunkaraHeinzHeinrichetal.2021, author = {Sunkara, Vikram and Heinz, Gitta A. and Heinrich, Frederik F. and Durek, Pawel and Mobasheri, Ali and Mashreghi, Mir-Farzin and Lang, Annemarie}, title = {Combining segmental bulk- and single-cell RNA-sequencing to define the chondrocyte gene expression signature in the murine knee joint}, volume = {29}, journal = {Osteoarthritis and Cartilage}, number = {6}, doi = {10.1016/j.joca.2021.03.007}, pages = {905 -- 914}, year = {2021}, language = {en} } @article{LueckeLuQuevedo2022, author = {L{\"u}cke, Marvin and Lu, Jingyi and Quevedo, Daniel E.}, title = {Coding for secrecy in remote state estimation with an adversary}, volume = {67}, journal = {IEEE Transactions on Automatic Control}, number = {9}, doi = {10.1109/TAC.2022.3169839}, pages = {4955 -- 4962}, year = {2022}, abstract = {We study the problem of remote state estimation in the presence of an eavesdropper. A sensor transmits state information over a packet-dropping link to a legitimate user. This information is randomly overheard by an eavesdropper. To reduce information leakage to the eavesdropper, previous studies have shown that by encoding the estimate with the acknowledgments (Acks), perfect secrecy can be achieved. However, this strategy greatly relies on the accuracy of the Acks and may easily fail if the Acks are compromised by cyberattacks. In this article, we tackle this issue by proposing to switch between sending an encoded state and sending the plain state to stay resilient against fake Acks. Specifically, we assume the Acks to be randomly attacked and derive recursive expressions for the minimum-mean-squared error estimates and error covariance matrices at the legitimate user and at the eavesdropper. Based upon this, we propose a transmission policy that depends on the probability of synchronization. We formulate a partially observable Markov decision process to model the evolution of the synchronization status and derive associated optimal transmission policies. Numerical examples are provided to verify the theoretical results.}, language = {en} } @article{FroehlerElberfeldMoelleretal.2020, author = {Fr{\"o}hler, Bernhard and Elberfeld, Tim and M{\"o}ller, Torsten and Hege, Hans-Christian and De Beenhouwer, Jan and Sijbers, Jan and Kastner, Johann and Heinzl, Christoph}, title = {Analysis and comparison of algorithms for the tomographic reconstruction of curved fibres}, volume = {35}, journal = {Nondestructive Testing and Evaluation}, number = {3}, doi = {10.1080/10589759.2020.1774583}, pages = {328 -- 341}, year = {2020}, abstract = {We present visual methods for the analysis and comparison of the results of curved fibre reconstruction algorithms, i.e., of algorithms extracting characteristics of curved fibres from X-ray computed tomography scans. In this work, we extend previous methods for the analysis and comparison of results of different fibre reconstruction algorithms or parametrisations to the analysis of curved fibres. We propose fibre dissimilarity measures for such curved fibres and apply these to compare multiple results to a specified reference. We further propose visualisation methods to analyse differences between multiple results quantitatively and qualitatively. In two case studies, we show that the presented methods provide valuable insights for advancing and parametrising fibre reconstruction algorithms, and support in improving their results in characterising curved fibres.}, language = {en} } @phdthesis{Eshtewy2020, author = {Eshtewy, Neveen Ali Salem}, title = {Mathematical Modeling of Metabolic-Genetic Networks}, year = {2020}, language = {en} } @article{LangHelfmeierStefanowskietal.2020, author = {Lang, Annemarie and Helfmeier, Sarah and Stefanowski, Jonathan and Kuppe, Aditi and Sunkara, Vikram and Pfeiffenberger, Moritz and Wolter, Angelique and Damerau, Alexandra and Hemmati-Sadeghi, Shabnam and Ringe, Jochen and Haag, Rainer and Hauser, Anja E. and L{\"o}hning, Max and Perka, Carsten and Duda, Georg and Hoff, Paula and Schmidt-Bleek, Katharina and Gaber, Timo and Buttgereit, Frank}, title = {HIF-stabilization prevents delayed fracture healing}, journal = {bioarxiv}, doi = {10.1101/2020.07.02.182832}, year = {2020}, language = {en} } @inproceedings{ShinanoTateiwaNakamuraetal.2020, author = {Shinano, Yuji and Tateiwa, N. and Nakamura, S. and Yoshida, A. and Yasuda, M. and Kaji, S. and Fujisawa, K.}, title = {Massive Parallelization for Finding Shortest Lattice Vectors Based on Ubiquity Generator Framework}, booktitle = {2020 SC20: International Conference for High Performance Computing, Networking, Storage and Analysis (SC)}, doi = {10.1109/SC41405.2020.00064}, pages = {834 -- 848}, year = {2020}, abstract = {Lattice-based cryptography has received attention as a next-generation encryption technique, because it is believed to be secure against attacks by classical and quantum computers. Its essential security depends on the hardness of solving the shortest vector problem (SVP). In the cryptography, to determine security levels, it is becoming significantly more important to estimate the hardness of the SVP by high-performance computing. In this study, we develop the world's first distributed and asynchronous parallel SVP solver, the MAssively Parallel solver for SVP (MAP-SVP). It can parallelize algorithms for solving the SVP by applying the Ubiquity Generator framework, which is a generic framework for branch-and-bound algorithms. The MAP-SVP is suitable for massive-scale parallelization, owing to its small memory footprint, low communication overhead, and rapid checkpoint and restart mechanisms. We demonstrate its performance and scalability of the MAP-SVP by using up to 100,032 cores to solve instances of the Darmstadt SVP Challenge.}, language = {en} } @inproceedings{PfetschPokutta2020, author = {Pfetsch, Marc and Pokutta, Sebastian}, title = {IPBoost - Non-Convex Boosting via Integer Programming}, booktitle = {Proceedings of ICML}, arxiv = {http://arxiv.org/abs/2002.04679}, year = {2020}, language = {en} } @inproceedings{PokuttaSinghTorrico2020, author = {Pokutta, Sebastian and Singh, M. and Torrico, A.}, title = {On the Unreasonable Effectiveness of the Greedy Algorithm: Greedy Adapts to Sharpness}, booktitle = {Proceedings of ICML}, arxiv = {http://arxiv.org/abs/2002.04063}, year = {2020}, language = {en} } @inproceedings{DiakonikolasCardereraPokutta2020, author = {Diakonikolas, Jelena and Carderera, Alejandro and Pokutta, Sebastian}, title = {Locally Accelerated Conditional Gradients}, booktitle = {Proceedings of AISTATS}, arxiv = {http://arxiv.org/abs/1906.07867}, year = {2020}, language = {en} } @article{FaenzaMunozPokutta2020, author = {Faenza, Yuri and Mu{\~n}oz, Gonzalo and Pokutta, Sebastian}, title = {New Limits of Treewidth-based tractability in Optimization}, volume = {191}, journal = {Mathematical Programming}, arxiv = {http://arxiv.org/abs/1807.02551}, doi = {10.1007/s10107-020-01563-5}, pages = {559 -- 594}, year = {2020}, language = {en} } @article{AnariHaghtalabNaoretal.2020, author = {Anari, N. and Haghtalab, N. and Naor, S. and Pokutta, Sebastian and Singh, M. and Torrico, A.}, title = {Structured Robust Submodular Maximization: Offline and Online Algorithms}, journal = {INFORMS Journal on Computing}, arxiv = {http://arxiv.org/abs/1710.04740}, year = {2020}, language = {en} } @inproceedings{CombettesPokutta2020, author = {Combettes, Cyrille W. and Pokutta, Sebastian}, title = {Boosting Frank-Wolfe by Chasing Gradients}, booktitle = {Proceedings of ICML}, arxiv = {http://arxiv.org/abs/2003.06369}, year = {2020}, language = {en} } @inproceedings{Pokutta2020, author = {Pokutta, Sebastian}, title = {Restarting Algorithms: Sometimes there is Free Lunch}, booktitle = {Proceedings of CPAIOR}, arxiv = {http://arxiv.org/abs/2006.14810}, year = {2020}, language = {en} } @article{LaydonSunkaraBoelenetal.2020, author = {Laydon, Daniel J. and Sunkara, Vikram and Boelen, Lies and Bangham, Charles R. M. and Asquith, Becca}, title = {The relative contributions of infectious and mitotic spread to HTLV-1 persistence}, journal = {PLOS Computational Biology}, doi = {10.1371/journal.pcbi.1007470}, year = {2020}, language = {en} } @article{KossenHirzelMadaietal.2022, author = {Kossen, Tabea and Hirzel, Manuel A. and Madai, Vince I. and Boenisch, Franziska and Hennemuth, Anja and Hildebrand, Kristian and Pokutta, Sebastian and Sharma, Kartikey and Hilbert, Adam and Sobesky, Jan and Galinovic, Ivana and Khalil, Ahmed A. and Fiebach, Jochen B. and Frey, Dietmar}, title = {Towards Sharing Brain Images: Differentially Private TOF-MRA Images with Segmentation Labels Using Generative Adversarial Networks}, journal = {Frontiers in Artificial Intelligence}, doi = {https://doi.org/10.3389/frai.2022.813842}, year = {2022}, abstract = {Sharing labeled data is crucial to acquire large datasets for various Deep Learning applications. In medical imaging, this is often not feasible due to privacy regulations. Whereas anonymization would be a solution, standard techniques have been shown to be partially reversible. Here, synthetic data using a Generative Adversarial Network (GAN) with differential privacy guarantees could be a solution to ensure the patient's privacy while maintaining the predictive properties of the data. In this study, we implemented a Wasserstein GAN (WGAN) with and without differential privacy guarantees to generate privacy-preserving labeled Time-of-Flight Magnetic Resonance Angiography (TOF-MRA) image patches for brain vessel segmentation. The synthesized image-label pairs were used to train a U-net which was evaluated in terms of the segmentation performance on real patient images from two different datasets. Additionally, the Fr{\´e}chet Inception Distance (FID) was calculated between the generated images and the real images to assess their similarity. During the evaluation using the U-Net and the FID, we explored the effect of different levels of privacy which was represented by the parameter ϵ. With stricter privacy guarantees, the segmentation performance and the similarity to the real patient images in terms of FID decreased. Our best segmentation model, trained on synthetic and private data, achieved a Dice Similarity Coefficient (DSC) of 0.75 for ϵ = 7.4 compared to 0.84 for ϵ = ∞ in a brain vessel segmentation paradigm (DSC of 0.69 and 0.88 on the second test set, respectively). We identified a threshold of ϵ <5 for which the performance (DSC <0.61) became unstable and not usable. Our synthesized labeled TOF-MRA images with strict privacy guarantees retained predictive properties necessary for segmenting the brain vessels. Although further research is warranted regarding generalizability to other imaging modalities and performance improvement, our results mark an encouraging first step for privacy-preserving data sharing in medical imaging.}, language = {en} } @article{RaharinirinaAcevedoTrejosMerico2022, author = {Raharinirina, N. Alexia and Acevedo-Trejos, Esteban and Merico, Agostino}, title = {Modelling the acclimation capacity of coral reefs to a warming ocean}, journal = {PLOS COMPUTATIONAL BIOLOGY}, doi = {10.1371/journal.pcbi.1010099}, year = {2022}, abstract = {The symbiotic relationship between corals and photosynthetic algae is the foundation of coral reef ecosystems. This relationship breaks down, leading to coral death, when sea temperature exceeds the thermal tolerance of the coral-algae complex. While acclimation via phenotypic plasticity at the organismal level is an important mechanism for corals to cope with global warming, community-based shifts in response to acclimating capacities may give valuable indications about the future of corals at a regional scale. Reliable regional-scale predictions, however, are hampered by uncertainties on the speed with which coral communities will be able to acclimate. Here we present a trait-based, acclimation dynamics model, which we use in combination with observational data, to provide a first, crude estimate of the speed of coral acclimation at the community level and to investigate the effects of different global warming scenarios on three iconic reef ecosystems of the tropics: Great Barrier Reef, South East Asia, and Caribbean. The model predicts that coral acclimation may confer some level of protection by delaying the decline of some reefs such as the Great Barrier Reef. However, the current rates of acclimation will not be sufficient to rescue corals from global warming. Based on our estimates of coral acclimation capacities, the model results suggest substantial declines in coral abundances in all three regions, ranging from 12\% to 55\%, depending on the region and on the climate change scenario considered. Our results highlight the importance and urgency of precise assessments and quantitative estimates, for example through laboratory experiments, of the natural acclimation capacity of corals and of the speed with which corals may be able to acclimate to global warming.}, language = {en} } @article{BeckerTeepleCharlesetal.2022, author = {Becker, Kaitlyn P and Teeple, Clark and Charles, Nicholas and Jung, Yeonsu and Baum, Daniel and Weaver, James C and Mahadevan, L. and Wood, Robert J}, title = {Active entanglement enables stochastic, topological grasping}, volume = {119}, journal = {PNAS}, number = {42}, doi = {10.1073/pnas.2209819119}, pages = {e2209819119}, year = {2022}, abstract = {Grasping, in both biological and engineered mechanisms, can be highly sensitive to the gripper and object morphology, as well as perception and motion planning. Here we circumvent the need for feedback or precise planning by using an array of fluidically-actuated slender hollow elastomeric filaments to actively entangle with objects that vary in geometric and topological complexity. The resulting stochastic interactions enable a unique soft and conformable grasping strategy across a range of target objects that vary in size, weight, and shape. We experimentally evaluate the grasping performance of our strategy, and use a computational framework for the collective mechanics of flexible filaments in contact with complex objects to explain our findings. Overall, our study highlights how active collective entanglement of a filament array via an uncontrolled, spatially distributed scheme provides new options for soft, adaptable grasping.}, language = {en} } @inproceedings{BernerRichterUllrich2024, author = {Berner, Julius and Richter, Lorenz and Ullrich, Karen}, title = {An optimal control perspective on diffusion-based generative modeling}, booktitle = {Transactions on Machine Learning Research}, year = {2024}, abstract = {We establish a connection between stochastic optimal control and generative models based on stochastic differential equations (SDEs) such as recently developed diffusion probabilistic models. In particular, we derive a Hamilton-Jacobi-Bellman equation that governs the evolution of the log-densities of the underlying SDE marginals. This perspective allows to transfer methods from optimal control theory to generative modeling. First, we show that the evidence lower bound is a direct consequence of the well-known verification theorem from control theory. Further, we develop a novel diffusion-based method for sampling from unnormalized densities -- a problem frequently occurring in statistics and computational sciences.}, language = {en} } @article{NueskenRichter2023, author = {N{\"u}sken, Nikolas and Richter, Lorenz}, title = {Interpolating between BSDEs and PINNs: deep learning for elliptic and parabolic boundary value problems}, volume = {2}, journal = {Journal of Machine Learning}, number = {1}, arxiv = {http://arxiv.org/abs/2112.03749}, doi = {0.4208/jml.220416}, pages = {31 -- 64}, year = {2023}, abstract = {Solving high-dimensional partial differential equations is a recurrent challenge in economics, science and engineering. In recent years, a great number of computational approaches have been developed, most of them relying on a combination of Monte Carlo sampling and deep learning based approximation. For elliptic and parabolic problems, existing methods can broadly be classified into those resting on reformulations in terms of backward stochastic differential equations (BSDEs) and those aiming to minimize a regression-type L2-error (physics-informed neural networks, PINNs). In this paper, we review the literature and suggest a methodology based on the novel diffusion loss that interpolates between BSDEs and PINNs. Our contribution opens the door towards a unified understanding of numerical approaches for high-dimensional PDEs, as well as for implementations that combine the strengths of BSDEs and PINNs. The diffusion loss furthermore bears close similarities to (least squares) temporal difference objectives found in reinforcement learning. We also discuss eigenvalue problems and perform extensive numerical studies, including calculations of the ground state for nonlinear Schr ¨odinger operators and committor functions relevant in molecular dynamics.}, language = {en} } @article{HartmannRichter2024, author = {Hartmann, Carsten and Richter, Lorenz}, title = {Nonasymptotic bounds for suboptimal importance sampling}, volume = {12}, journal = {SIAM/ASA Journal on Uncertainty Quantification}, number = {2}, arxiv = {http://arxiv.org/abs/2102.09606}, doi = {10.1137/21M1427760}, pages = {309 -- 346}, year = {2024}, abstract = {Importance sampling is a popular variance reduction method for Monte Carlo estimation, where an evident question is how to design good proposal distributions. While in most cases optimal (zero-variance) estimators are theoretically possible, in practice only suboptimal proposal distributions are available and it can often be observed numerically that those can reduce statistical performance significantly, leading to large relative errors and therefore counteracting the original intention. Previous analysis on importance sampling has often focused on asymptotic arguments that work well in a large deviations regime. In this article, we provide lower and upper bounds on the relative error in a nonasymptotic setting. They depend on the deviation of the actual proposal from optimality, and we thus identify potential robustness issues that importance sampling may have, especially in high dimensions. We particularly focus on path sampling problems for diffusion processes with nonvanishing noise, for which generating good proposals comes with additional technical challenges. We provide numerous numerical examples that support our findings and demonstrate the applicability of the derived bounds.}, language = {en} } @article{KamčevSpiegel2022, author = {Kamčev, Nina and Spiegel, Christoph}, title = {Another note on intervals in the Hales-Jewett theorem}, volume = {29}, journal = {Electronic Journal of Combinatorics}, number = {1}, doi = {10.37236/6730}, pages = {P1.62}, year = {2022}, abstract = {The Hales-Jewett Theorem states that any r-colouring of [m]ⁿ contains a monochromatic combinatorial line if n is large enough. Shelah's proof of the theorem implies that for m = 3 there always exists a monochromatic combinatorial line whose set of active coordinates is the union of at most r intervals. For odd r, Conlon and Kamčev constructed r-colourings for which it cannot be fewer than r intervals. However, we show that for even r and large n, any r-colouring of [3]ⁿ contains a monochromatic combinatorial line whose set of active coordinates is the union of at most r-1 intervals. This is optimal and extends a result of Leader and R{\"a}ty for r=2.}, language = {en} } @article{SunkaraLewisNguyenetal.2022, author = {Sunkara, Vikram and Lewis, Angus and Nguyen, Giang T. and O'Reilly, Malgorzata M. and Bean, Nigel}, title = {A discontinuous Galerkin method for approximating the stationary distribution of stochastic fluid-fluid processes}, journal = {Methodology and Computing in Applied Probability}, doi = {10.1007/s11009-022-09945-2}, year = {2022}, language = {en} } @article{LangVesterFerreiraGomesetal.2022, author = {Lang, Annemarie and Vester, Antja and Ferreira-Gomes, M. and Guerra, G.M. and Heinrich, Fredrich R. and G{\"o}tzke, C.C. and Kurmies, Sebastian and Sunkara, Vikram and Durek, Pawel and Boerckel, Joel D. and Mashreghi, Mir-Farzin}, title = {PIPELINE FOR SINGLE CELL SEQUENCING OF HUMAN CHONDROCYTE PELLET CULTURES TO DELINEATE IL-1β MODULATED CHANGES IN CELL HETEROGENEITY}, volume = {30}, journal = {Osteoarthritis and Cartilage}, number = {Supplement 1}, doi = {10.1016/j.joca.2022.02.112}, pages = {S90}, year = {2022}, language = {en} } @inproceedings{RichterBerner2022, author = {Richter, Lorenz and Berner, Julius}, title = {Robust SDE-Based Variational Formulations for Solving Linear PDEs via Deep Learning}, volume = {162}, booktitle = {Proceedings of the 39th International Conference on Machine Learning, PMLR}, pages = {18649 -- 18666}, year = {2022}, abstract = {The combination of Monte Carlo methods and deep learning has recently led to efficient algorithms for solving partial differential equations (PDEs) in high dimensions. Related learning problems are often stated as variational formulations based on associated stochastic differential equations (SDEs), which allow the minimization of corresponding losses using gradient-based optimization methods. In respective numerical implementations it is therefore crucial to rely on adequate gradient estimators that exhibit low variance in order to reach convergence accurately and swiftly. In this article, we rigorously investigate corresponding numerical aspects that appear in the context of linear Kolmogorov PDEs. In particular, we systematically compare existing deep learning approaches and provide theoretical explanations for their performances. Subsequently, we suggest novel methods that can be shown to be more robust both theoretically and numerically, leading to substantial performance improvements.}, language = {en} } @inproceedings{KruegerManleyZschiedrichetal.2022, author = {Kr{\"u}ger, Jan and Manley, Phillip and Zschiedrich, Lin and Hammerschmidt, Martin and Schneider, Philipp-Immanuel and K{\"o}ning, Rainer and Bodermann, Bernd}, title = {Untersuchung des Schwingungseinflusses auf gemessene Punktspreizfunktionen in der optischen Mikroskopie}, booktitle = {Proc. DGaO}, url = {http://nbn-resolving.de/urn:nbn:de:0287-2022-P005-6}, pages = {P5}, year = {2022}, language = {en} } @article{ReidelbachBaiZoellneretal.2022, author = {Reidelbach, Marco and Bai, Mei and Z{\"o}llner, Martin Sebastian and Schneeberger, Michaela and Kubicek, Katharina and Kirchberg, Henning and Bressler, Christian and Thorwart, Michael and Herrmann, Carmen}, title = {Solvent dynamics of aqueous halides before and after photoionization}, journal = {Journal of Physical Chemistry}, year = {2022}, language = {en} } @inproceedings{SharmaHendrychBesanconetal.2024, author = {Sharma, Kartikey and Hendrych, Deborah and Besan{\c{c}}on, Mathieu and Pokutta, Sebastian}, title = {Network Design for the Traffic Assignment Problem with Mixed-Integer Frank-Wolfe}, booktitle = {Proceedings of INFORMS Optimization Society Conference}, year = {2024}, language = {en} } @article{MukherjeeKerteszZolnaietal.2025, author = {Mukherjee, Deshabrato and Kert{\´e}sz, Kriszti{\´a}n and Zolnai, Zsolt and Kov{\´a}cs, Zolt{\´a}n and De{\´a}k, Andr{\´a}s and P{\´a}link{\´a}s, Andr{\´a}s and Osv{\´a}th, Zolt{\´a}n and Olasz, D{\´a}niel and Romanenko, Alekszej and Fried, Mikl{\´o}s and Burger, Sven and S{\´a}fr{\´a}n, Gy{\"o}rgy and Petrik, Peter}, title = {Optimized Sensing on Gold Nanoparticles Created by Graded-Layer Magnetron Sputtering and Annealing}, volume = {425}, journal = {Sens. Actuators B Chem.}, doi = {10.1016/j.snb.2024.136875}, pages = {136875}, year = {2025}, language = {en} } @article{GaskinConradPavliotisetal.2024, author = {Gaskin, Thomas and Conrad, Tim and Pavliotis, Grigorios A. and Sch{\"u}tte, Christof}, title = {Neural parameter calibration and uncertainty quantification for epidemic forecasting}, volume = {19}, journal = {PLOS ONE}, number = {10}, arxiv = {http://arxiv.org/abs/2312.03147}, doi = {10.1371/journal.pone.0306704}, year = {2024}, abstract = {The recent COVID-19 pandemic has thrown the importance of accurately forecasting contagion dynamics and learning infection parameters into sharp focus. At the same time, effective policy-making requires knowledge of the uncertainty on such predictions, in order, for instance, to be able to ready hospitals and intensive care units for a worst-case scenario without needlessly wasting resources. In this work, we apply a novel and powerful computational method to the problem of learning probability densities on contagion parameters and providing uncertainty quantification for pandemic projections. Using a neural network, we calibrate an ODE model to data of the spread of COVID-19 in Berlin in 2020, achieving both a significantly more accurate calibration and prediction than Markov-Chain Monte Carlo (MCMC)-based sampling schemes. The uncertainties on our predictions provide meaningful confidence intervals e.g. on infection figures and hospitalisation rates, while training and running the neural scheme takes minutes where MCMC takes hours. We show convergence of our method to the true posterior on a simplified SIR model of epidemics, and also demonstrate our method's learning capabilities on a reduced dataset, where a complex model is learned from a small number of compartments for which data is available.}, language = {en} } @article{SteudleWinkelmannFuerstetal.2024, author = {Steudle, Gesine and Winkelmann, Stefanie and F{\"u}rst, Steffen and Wolf, Sarah}, title = {Understanding Memory Mechanisms in Socio-Technical Systems: the Case of an Agent-based Mobility Model}, volume = {27}, journal = {Advances in Complex Systems}, doi = {10.1142/S0219525924400034}, year = {2024}, abstract = {This paper explores memory mechanisms in complex socio-technical systems, using a mobility demand model as an example case. We simplified a large-scale agent-based mobility model into a Markov process and discover that the mobility decision process is non-Markovian. This is due to its dependence on the system's history, including social structure and local infrastructure, which evolve based on prior mobility decisions. To make the process Markovian, we extend the state space by incorporating two history-dependent components. Although our model is a very much reduced version of the original one, it remains too complex for the application of usual analytic methods. Instead, we employ simulations to examine the functionalities of the two history-dependent components. We think that the structure of the analyzed stochastic process is exemplary for many socio-technical, -economic, -ecological systems. Additionally, it exhibits analogies with the framework of extended evolution, which has previously been used to study cultural evolution.}, language = {en} } @article{BraunGuzmanPokutta2024, author = {Braun, G{\´a}bor and Guzm{\´a}n, Crist{\´o}bal and Pokutta, Sebastian}, title = {Corrections to "Lower Bounds on the Oracle Complexity of Nonsmooth Convex Optimization via Information Theory"}, volume = {70}, journal = {IEEE Transactions on Information Theory}, number = {7}, doi = {10.1109/TIT.2024.3357200}, pages = {5408 -- 5409}, year = {2024}, abstract = {This note closes a gap in the proof of Theorem VI.3 from the article "Lower Bounds on the Oracle Complexity of Nonsmooth Convex Optimization via Information Theory" (2017).}, language = {en} } @phdthesis{Chewle2023, author = {Chewle, Surahit}, title = {Probing effects of organic solvents on paracetamol crystallization using in silico and orthogonal in situ methods}, year = {2023}, abstract = {Polymorphism is the property exhibited by many inorganic and organic molecules to crystallize in more than one crystal structure. There is a strong need for understanding the influencing factors on polymorphism, as it is responsible for differences in many physicochemical properties such as stability and solubility. Nearly 80 \% of marketed drugs exhibit polymorphism. In this work, we took the model system of paracetamol to investigate the influence of solvent choice on its polymorphism. Different methods were developed and employed to understand the influence of small organic solvents on the crystallization of paracetamol. Non-equilibrium molecular dynamics simulations with periodic simulated annealing were used as a tool to probe the nature of precursors of the metastable intermediates occurring in the crystallization process. Using this method, it was found that the structures of the building blocks of crystals of paracetamol is governed by solvent-solute interactions. In situ Raman spectroscopy was used with a custom-made acoustic levitator to follow crystallization. This set-up is a reliable method for investigating solvent influence, attenuating heterogeneous nucleation and stabilizing other environmental factors. It was established that as a solvent, ethanol is much stronger than methanol in its effect of driving paracetamol solutions to their crystal form. The time-resolved Raman spectroscopy crystallization data was processed using a newly developed objective function based non-negative matrix factorization method (NMF). An orthogonal time-lapse photography was used in conjunction with NMF to get unique and accurate factors that pertain to the spectra and concentrations of different moieties of paracetamol crystallization existing as latent components in the untreated data.}, language = {en} } @article{LamboKoyanagiRagyanszkietal.2023, author = {Lambo, Ricardo Lewis and Koyanagi, Gregory K. and Ragyanszki, Anita and Horbatsch, Marko and Fournier, Rene and Hessels, Eric A.}, title = {Calculation of the local environment of a barium monofluoride molecule in an argon matrix: a step towards using matrix-isolated BaF for determining the electron electric dipole moment}, volume = {121}, journal = {Molecular Physics}, number = {6}, doi = {10.1080/00268976.2023.2198044}, year = {2023}, language = {en} } @article{KoyanagiLamboRagyanszkietal.2023, author = {Koyanagi, Gregory K. and Lambo, Ricardo Lewis and Ragyanszki, Anita and Fournier, Rene A. and Horbatsch, Marko W. and Hessels, Eric A.}, title = {Accurate calculation of the interaction of a barium monofluoride molecule with an argon atom: A step towards using matrix isolation of BaF for determining the electron electric dipole moment}, volume = {391}, journal = {Journal of Molecular Spectroscopy}, doi = {10.1016/j.jms.2023.111736}, pages = {111736}, year = {2023}, language = {en} } @article{TrepteSeckerKostovaetal.2023, author = {Trepte, Philipp and Secker, Christopher and Kostova, Simona and Maseko, Sibusiso B. and Gang Choi, Soon and Blavier, Jeremy and Minia, Igor and Silva Ramos, Eduardo and Cassonnet, Patricia and Golusik, Sabrina and Zenkner, Martina and Beetz, Stephanie and Liebich, Mara J. and Scharek, Nadine and Sch{\"u}tz, Anja and Sperling, Marcel and Lisurek, Michael and Wang, Yang and Spirohn, Kerstin and Hao, Tong and Calderwood, Michael A. and Hill, David E. and Landthaler, Markus and Olivet, Julien and Twizere, Jean-Claude and Vidal, Marc and Wanker, Erich E.}, title = {AI-guided pipeline for protein-protein interaction drug discovery identifies a SARS-CoV-2 inhibitor}, journal = {bioRxiv}, doi = {10.1101/2023.06.14.544560}, year = {2023}, language = {en} } @article{KraemerDurumericCharronetal.2023, author = {Kr{\"a}mer, Andreas and Durumeric, Aleksander and Charron, Nicholas and Chen, Yaoyi and Clementi, Cecilia and No{\´e}, Frank}, title = {Statistically optimal force aggregation for coarse-graining molecular dynamics}, volume = {14}, journal = {The Journal of Physical Chemistry Letters}, number = {17}, doi = {10.1021/acs.jpclett.3c00444}, pages = {3970 -- 3979}, year = {2023}, abstract = {Machine-learned coarse-grained (CG) models have the potential for simulating large molecular complexes beyond what is possible with atomistic molecular dynamics. However, training accurate CG models remains a challenge. A widely used methodology for learning bottom-up CG force fields maps forces from all-atom molecular dynamics to the CG representation and matches them with a CG force field on average. We show that there is flexibility in how to map all-atom forces to the CG representation and that the most commonly used mapping methods are statistically inefficient and potentially even incorrect in the presence of constraints in the all-atom simulation. We define an optimization statement for force mappings and demonstrate that substantially improved CG force fields can be learned from the same simulation data when using optimized force maps. The method is demonstrated on the miniproteins chignolin and tryptophan cage and published as open-source code.}, language = {en} } @article{DurumericCharronTempletonetal.2023, author = {Durumeric, Aleksander and Charron, Nicholas and Templeton, Clark and Musil, F{\´e}lix and Bonneau, Klara and Pasos-Trejo, Aldo and Chen, Yaoyi and Kelkar, Atharva and No{\´e}, Frank and Clementi, Cecilia}, title = {Machine learned coarse-grained protein force-fields: Are we there yet?}, volume = {79}, journal = {Current Opinion in Structural Biology}, doi = {10.1016/j.sbi.2023.102533}, year = {2023}, abstract = {The successful recent application of machine learning methods to scientific problems includes the learning of flexible and accurate atomic-level force-fields for materials and biomolecules from quantum chemical data. In parallel, the machine learning of force-fields at coarser resolutions is rapidly gaining relevance as an efficient way to represent the higher-body interactions needed in coarse-grained force-fields to compensate for the omitted degrees of freedom. Coarse-grained models are important for the study of systems at time and length scales exceeding those of atomistic simulations. However, the development of transferable coarse-grained models via machine learning still presents significant challenges. Here, we discuss recent developments in this field and current efforts to address the remaining challenges.}, language = {en} } @article{MajewskiPerezThoelkeetal.2023, author = {Majewski, Maciej and P{\´e}rez, Adri{\`a} and Th{\"o}lke, Philipp and Doerr, Stefan and Charron, Nicholas and Giorgino, Toni and Husic, Brooke and Clementi, Cecilia and No{\´e}, Frank and De Fabritiis, Gianni}, title = {Machine learning coarse-grained potentials of protein thermodynamics}, volume = {14}, journal = {Nature Communications}, doi = {10.1038/s41467-023-41343-1}, year = {2023}, abstract = {A generalized understanding of protein dynamics is an unsolved scientific problem, the solution of which is critical to the interpretation of the structure-function relationships that govern essential biological processes. Here, we approach this problem by constructing coarse-grained molecular potentials based on artificial neural networks and grounded in statistical mechanics. For training, we build a unique dataset of unbiased all-atom molecular dynamics simulations of approximately 9 ms for twelve different proteins with multiple secondary structure arrangements. The coarse-grained models are capable of accelerating the dynamics by more than three orders of magnitude while preserving the thermodynamics of the systems. Coarse-grained simulations identify relevant structural states in the ensemble with comparable energetics to the all-atom systems. Furthermore, we show that a single coarse-grained potential can integrate all twelve proteins and can capture experimental structural features of mutated proteins. These results indicate that machine learning coarse-grained potentials could provide a feasible approach to simulate and understand protein dynamics.}, language = {en} } @article{DesignolleVertesiPokutta2024, author = {Designolle, S{\´e}bastien and V{\´e}rtesi, Tam{\´a}s and Pokutta, Sebastian}, title = {Symmetric multipartite Bell inequalities via Frank-Wolfe algorithms}, volume = {109}, journal = {Physics Review A}, number = {2}, doi = {10.1103/PhysRevA.109.022205}, year = {2024}, abstract = {In multipartite Bell scenarios, we study the nonlocality robustness of the Greenberger-Horne-Zeilinger (GHZ) state. When each party performs planar measurements forming a regular polygon, we exploit the symmetry of the resulting correlation tensor to drastically accelerate the computation of (i) a Bell inequality via Frank-Wolfe algorithms and (ii) the corresponding local bound. The Bell inequalities obtained are facets of the symmetrized local polytope and they give the best-known upper bounds on the nonlocality robustness of the GHZ state for three to ten parties. Moreover, for four measurements per party, we generalize our facets and hence show, for any number of parties, an improvement on Mermin's inequality in terms of noise robustness. We also compute the detection efficiency of our inequalities and show that some give rise to the activation of nonlocality in star networks, a property that was only shown with an infinite number of measurements.}, language = {en} } @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} }