Publications 2020

  1. A

    1. Adam, S. ; Anteneh, H. ; Hornisch, M. ; Wagner, V. ; Lu, J. ; Radde, N. ; Bashtrykov, P. ; Song, J. ; u. a.: DNA sequence-dependent activity and base flipping mechanisms of DNMT1 regulate genome-wide DNA methylation. In: Nat. Communications, Nat. Communications. Bd. 11, Springer Science and Business Media LLC (2020), Nr. 1, S. 1–15
    2. Altmann, Robert ; Mehrmann, Volker ; Unger, Benjamin: Port-Hamiltonian formulations of poroelastic network models. In: ArXiv e-print 2012.01949, ArXiv e-print 2012.01949. (2020)
  2. B

    1. Bahlmann, L. M. ; Smits, K. M. ; Heck, K. ; Coltman, E. ; Helmig, R. ; Neuweiler, I.: Gas Component Transport Across the Soil-Atmosphere Interface for Gases of Different Density: Experiments and Modeling. In: Water Resources Research, Water Resources Research. Bd. 56 (2020), Nr. 9, S. e2020WR027600. — e2020WR027600 10.1029/2020WR027600
    2. Barreau, M. ; Scherer, C. W. ; Gouaisbaut, F. ; Seuret, A.: Integral Quadratic Constraints on Linear Infinite-dimensional Systems for Robust Stability Analysis. In: IFAC World Congress, IFAC World Congress. Bd. 53, 2020, S. 7752–7757
    3. Bauer, TL ; Buchholz, PCF ; Pleiss, J: The modular structure of α/β-hydrolases. In: FEBS J, FEBS J. Bd. 287 (2020), S. 1035–1053
    4. Beck, Andrea D. ; Zeifang, Jonas ; Schwarz, Anna ; Flad, David G.: A neural network based shock detection and localization approach for discontinuous Galerkin methods. In: Journal of Computational Physics, Journal of Computational Physics. Bd. 423, Elsevier (2020), S. 109824
    5. Beckers, Felix ; Heredia, Andrés ; Noack, Markus ; Nowak, Wolfgang ; Wieprecht, Silke ; Oladyshkin, Sergey: Bayesian Calibration and Validation of a Large-scale and Time-demanding Sediment Transport Model. In: Water Resources Research, Water Resources Research. Bd. 56 (2020), Nr. 7, S. e2019WR026966
    6. Berberich, J. ; Allgöwer, F.: A trajectory-based framework for data-driven system analysis and control. In: Proc. European Control Conf. (ECC), Proc. European Control Conf. (ECC). Saint Petersburg, Russia, 2020, S. 1365–1370
    7. Berberich, J. ; Köhler, J. ; Müller, M. A. ; Allgöwer, F.: Robust constraint satisfaction in data-driven MPC. In: Proc. 59th IEEE Conf. Decision and Control (CDC), Proc. 59th IEEE Conf. Decision and Control (CDC). Jeju, South Korea, 2020, S. 1260–1267
    8. Berberich, J. ; Köhler, J. ; Müller, M. A. ; Allgöwer, F.: Data-driven tracking MPC for changing setpoints. In: Proc. 21st IFAC World Congress, Proc. 21st IFAC World Congress. Berlin, Germany, 2020, S. 971–976
    9. Berberich, Julian ; Koch, Anne ; Scherer, Carsten W. ; Allgower, Frank: Robust data-driven state-feedback design. In: 2020 American Control Conference (ACC), 2020 American Control Conference (ACC) : IEEE, 2020, S. 1532–1538
    10. Berberich, Julian ; Scherer, Carsten W. ; Allgöwer, Frank: Combining Prior Knowledge and Data for Robust Controller Design (2020)
    11. Breitsprecher, Konrad ; Janssen, Mathijs ; Srimuk, Pattarachai ; Mehdi, B. Layla ; Presser, Volker ; Holm, Christian ; Kondrat, Svyatoslav: How to speed up ion transport in nanopores. In: Nature Communications, Nature Communications. Bd. 11, Springer Science and Business Media LLC (2020), Nr. 1
    12. Brencher, Lukas ; Barth, Andrea: Hyperbolic Conservation Laws with Stochastic Discontinuous Flux Functions. In: Klöfkorn, R. ; Keilegavlen, E. ; Radu, F. A. ; Fuhrmann, J. (Hrsg.) ; Klöfkorn, R. ; Keilegavlen, E. ; Radu, F. A. ; Fuhrmann, J. (Hrsg.): Finite Volumes for Complex Applications IX : Methods, Theoretical Aspects, Examples, Finite Volumes for Complex Applications IX : Methods, Theoretical Aspects, Examples : Springer, 2020 — ISBN 978-3-030-43650-6 and 978-3-030-43651-3, S. 265–273
    13. Buchfink, P. ; Haasdonk, B. ; Rave, S.: PSD-Greedy Basis Generation for Structure-Preserving Model Order Reduction of Hamiltonian Systems. In: Frolkovič, P. ; Mikula, K. ; Ševčovič, D. (Hrsg.) ; Frolkovič, P. ; Mikula, K. ; Ševčovič, D. (Hrsg.): Proceedings of the Conference Algoritmy 2020, Proceedings of the Conference Algoritmy 2020 : Vydavateľstvo SPEKTRUM, 2020 — ISBN 978-80-227-5032-5, S. 151--160
  3. C

    1. Chu, Xu ; Wu, Yongxiang ; Rist, Ulrich ; Weigand, Bernhard: Instability and transition in an elementary porous medium. In: Phys. Rev. Fluids, Phys. Rev. Fluids. Bd. 5, American Physical Society (2020), Nr. 4, S. 044304
    2. Chu, Xu (初旭) ; Liu, Yanchao (刘雁超) ; Wang, Wenkang (王文康) ; Yang, Guang (杨光) ; Weigand, Bernhard ; Nemati, Hassan: Turbulence, pseudo-turbulence, and local flow topology in dispersed bubbly flow. In: Physics of Fluids, Physics of Fluids. Bd. 32 (2020), Nr. 8, S. 083310
    3. Coltman, Edward ; Ackermann, Sina ; Becker, Beatrix ; Blatt, Markus ; Burbulla, Samuel ; Class, Holger ; Emmert, Simon ; Flemisch, Bernd ; u. a.: DuMuX 3.2.0, Zenodo (2020)
    4. Coltman, Edward ; Lipp, Melanie ; Vescovini, Andrea ; Helmig, Rainer: Obstacles, Interfacial Forms, and Turbulence: A Numerical Analysis of Soil--Water Evaporation Across Different Interfaces. In: Transport in Porous Media, Transport in Porous Media. Bd. 134, Springer (2020), Nr. 2, S. 275--301
    5. Cooper, A.M. ; Kästner, J. ; Urban, A. ; Artrith, N.: Efficient training of ANN potentials by including atomic forces via Taylor expansion and application to water and a transition-metal oxide. In: Npj Comput. Mater., Npj Comput. Mater. Bd. 6 (2020), S. 54
  4. D

    1. de Souza, Fábio A. L. ; Sivaraman, Ganesh ; Fyta, Maria ; Scheicher, Ralph H. ; Scopel, Wanderlã L. ; Amorim, Rodrigo G.: Electrically sensing Hachimoji DNA nucleotides through a hybrid graphene/h-BN nanopore. In: Nanoscale, Nanoscale. Bd. 12, The Royal Society of Chemistry (2020), Nr. 35, S. 18289–18295
    2. Denzel, Alexander ; Kästner, Johannes: Hessian Matrix Update Scheme for Transition State Search Based on Gaussian Process Regression. In: Journal of Chemical Theory and Computation, Journal of Chemical Theory and Computation. Bd. 16, American Chemical Society (ACS) (2020), Nr. 8, S. 5083--5089
    3. Diestelkämper, Ralf ; Herschel, Melanie: Tracing nested data with structural provenance for big data analytics. In: Proceedings of the International Conference on Extending Database Technology (EDBT), Proceedings of the International Conference on Extending Database Technology (EDBT), 2020, S. 253–264
    4. Diestelkämper, Ralf ; Herschel, Melanie: Distributed Tree-Pattern Matching in Big Data Analytics Systems. In: In Proceedings of the Conference on Advances in Databases and Information Systems (ADBIS), In Proceedings of the Conference on Advances in Databases and Information Systems (ADBIS) : Springer, 2020, S. 171–186
  5. E

    1. Eisenkolb, I ; Jensch, A ; Eisenkolb, K ; Kramer, A ; Buchholz, Patrick ; Pleiss, Jürgen ; Spiess, A ; Radde, NE: Modeling of biocatalytic reactions: A workflow for model calibration, selection and validation using Bayesian statistics. In: AIChE J, AIChE J. Bd. 66 (2020), S. e16866
    2. Ejaz, Fahad ; Guthke, Anneli ; Wöhling, Thomas ; Nowak, Wolfgang: Comprehensive uncertainty analysis for surface water and groundwater projections under climate change based on a lumped geo-hydrological model. In: Journal of Hydrology, Journal of Hydrology. Bd. 626 (2023)
    3. Erdal, Daniel ; Xiao, Sinan ; Nowak, Wolfgang ; Cirpka, Olaf: Sampling Behavioral Model Parameters for Ensemble-based Sensitivity Analysis using Gaussian Process Emulation and Active Subspaces. In: Stochastic Environmental Research and Risk Assessment, Stochastic Environmental Research and Risk Assessment. Bd. 34 (2020), S. 1813–1830
    4. Escher, Joachim ; Knopf, Patrik ; Lienstromberg, Christina ; Matioc, Bogdan-Vasile: Stratified periodic water waves with singular density gradients. In: Ann. Mat. Pura Appl. (4), Ann. Mat. Pura Appl. (4). Bd. 199 (2020), Nr. 5, S. 1923--1959
  6. F

    1. Fernandez, Mauricio ; Fritzen, Felix: On the generation of periodic discrete structures with identical two-point correlation. In: Proceedings of the Royal Society A, Proceedings of the Royal Society A. Bd. 476, The Royal Society Publishing (2020), Nr. 2242, S. 20200568
    2. Fernández, Mauricio ; Fritzen, Felix: On the generation of periodic discrete structures with identical two-point correlation. In: Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences. Bd. 476 (2020), Nr. 2242, S. 20200568
    3. Fernández, Mauricio ; Fritzen, Felix: Construction of a class of sharp Löwner majorants for a set of symmetric matrices. In: Journal of Applied Mathematics, Journal of Applied Mathematics. Bd. 2020, Hindawi (2020), S. 1–18
    4. Fernández, Mauricio ; Rezaei, Shahed ; Mianroodi, Jaber Rezaei ; Fritzen, Felix ; Reese, Stefanie: Application of artificial neural networks for the prediction of interface mechanics: a study on grain boundary constitutive behavior. In: Advanced Modeling and Simulation in Engineering Sciences, Advanced Modeling and Simulation in Engineering Sciences. Bd. 7, Springer Science and Business Media LLC (2020), Nr. 1, S. 27
    5. Fischer, Matthias ; Bauer, Gernot ; Gross, Joachim: Transferable Anisotropic United-Atom Mie (TAMie) Force Field: Transport Properties from Equilibrium Molecular Dynamic Simulations. In: Industrial & Engineering Chemistry Research, Industrial & Engineering Chemistry Research. Bd. 59, ACS Publications (2020), Nr. 18, S. 8855--8869
    6. Flaig, Sascha: Prognose von Wasserständen in einem durch die Trinkwassergewinnung beeinflussten Moor-Grundwassersystem mithilfe eines künstlichen neuronalen Netzwerks : MSc Thesis, University of Stuttgart, 2020
    7. Flemisch, Bernd ; Hermann, Sibylle ; Holm, Christian ; Mehl, Miriam ; Reina, Guido ; Uekermann, Benjamin ; Boehringer, David ; Ertl, Thomas ; u. a.: Umgang mit Forschungssoftware an der Universität Stuttgart : Universität Stuttgart, 2020
    8. Fullstone, Gavin ; Bauer, Tabea L. ; Guttà, Cristiano ; Salvucci, Manuela ; Prehn, Jochen H. M. ; Rehm, Markus: The apoptosome molecular timer synergises with XIAP to suppress apoptosis execution and contributes to prognosticating survival in colorectal cancer. In: Cell Death & Differentiation, Cell Death & Differentiation. (2020), Nr. 27, S. 2828–2842
    9. Fullstone, Gavin ; Guttà, Cristiano ; Beyer, Amatus ; Rehm, Markus: The FLAME-accelerated signalling tool (FaST) for facile parallelisation of flexible agent-based models of cell signalling. In: npj Systems Biology and Applications, npj Systems Biology and Applications. Bd. 6 (2020), Nr. 1, S. 10--
  7. G

    1. Gebhardt, Julia ; Kiesel, Matthias ; Riniker, Sereina ; Hansen, Niels: Combining Molecular Dynamics and Machine Learning to Predict Self-Solvation Free Energies and Limiting Activity Coefficients. In: Journal of Chemical Information and Modeling, Journal of Chemical Information and Modeling. Bd. 60, American Chemical Society (ACS) (2020), Nr. 11, S. 5319--5330
    2. Guisandez, Ignacio ; Perez-Diaz, Juan Ignacio ; Nowak, Wolfgang ; Haas, Jannik: Should environmental constraints be considered in linear programming based water value calculators? In: International Journal of Electrical Power & Energy Systems, International Journal of Electrical Power & Energy Systems. Bd. 117 (2020), Nr. 105662
    3. Guttà, Cristiano ; Rahman, Arman ; Aura, Claudia ; Dynoodt, Peter ; Charles, Emilie M. ; Hirschenhahn, Elodie ; Joseph, Jesuchristopher ; Wouters, Jasper ; u. a.: Low expression of pro-apoptotic proteins Bax, Bak and Smac indicates prolonged progression-free survival in chemotherapy-treated metastatic melanoma. In: Cell Death & Disease, Cell Death & Disease. Bd. 11, Springer Science and Business Media LLC (2020), Nr. 2
    4. Gygli, G ; Pleiss, Jürgen: Simulation Foundry: automated and F.A.I.R. molecular modelling. In: J Chem Inf Model, J Chem Inf Model. Bd. 60 (2020), S. 1922–1927
    5. Gygli, G ; Xu, XM ; Pleiss, Jürgen: Meta-analysis of viscosity of aqueous deep eutectic solvents and their components. In: Sci Rep, Sci Rep. Bd. 10 (2020), S. 21395–21395
    6. Gygli, Gudrun ; Pleiss, Juergen: Simulation foundry: Automated and FAIR molecular modeling. In: Journal of chemical information and modeling, Journal of chemical information and modeling. Bd. 60, ACS Publications (2020), Nr. 4, S. 1922--1927
  8. H

    1. Hansen, Niels ; Öehlknecht, Christoph ; de Ruiter, Anita ; Lier, Bettina ; van Gunsteren, Wilfred F. ; Oostenbrink, Chris ; Gebhardt, Julia: A Suite of Advanced Tutorials for the GROMOS Biomolecular Simulation Software Article v1.0. In: Living Journal of Computational Molecular Science, Living Journal of Computational Molecular Science. Bd. 2, University of Colorado at Boulder (2020), Nr. 1
    2. Hasan, Sharul ; Niasar, Vahid ; Karadimitriou, Nikolaos K ; Godinho, Jose RA ; Vo, Nghia T ; An, Senyou ; Rabbani, Arash ; Steeb, Holger: Direct characterization of solute transport in unsaturated porous media using fast X-ray synchrotron microtomography. In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences. Bd. 117, National Acad Sciences (2020), Nr. 38, S. 23443--23449
    3. Heck, K. ; Coltman, E. ; Schneider, J. ; Helmig, R.: Influence of Radiation on Evaporation Rates: A Numerical Analysis. In: Water Resources Research, Water Resources Research. Bd. 56, American Geophysical Union (AGU) (2020), Nr. 10
    4. Hertneck, M. ; Allgöwer, F.: Exploiting Information for Decentralized Periodic Event-Triggered Control. In: Proc. 59th IEEE Conf. Decision and Control (CDC), Proc. 59th IEEE Conf. Decision and Control (CDC). Jeju, South Korea, 2020, S. 4999–5004
    5. Hertneck, M. ; Linsenmayer, S. ; Allgöwer, F.: Stability Analysis for Nonlinear Weakly Hard Real-Time Control Systems. In: Proc. 21st IFAC World Congress, Proc. 21st IFAC World Congress. Berlin, Germany, 2020, S. 2632–2637
    6. Hertneck, M. ; Linsenmayer, S. ; Allgöwer, F.: Model-Based Nonlinear Periodic Event-Triggered Control for Continuous-Time Systems with Sampled-Data Prediction. In: Proc. European Control Conf. (ECC), Proc. European Control Conf. (ECC). Saint Petersburg, Russia, 2020, S. 1814–1819
    7. Heyen, Frank ; Munz, Tanja ; Neumann, Michael ; Ortega, Daniel ; Vu, Ngoc Thang ; Weiskopf, Daniel ; Sedlmair, Michael: ClaVis: An Interactive Visual Comparison System for Classifiers. In: Proceedings of the International Conference on Advanced Visual Interfaces, Proceedings of the International Conference on Advanced Visual Interfaces, 2020, S. 1--9
    8. Hilder, Bastian: Modulating traveling fronts for the Swift-Hohenberg equation in the case of an additional conservation law. In: Journal of Differential Equations, Journal of Differential Equations. Bd. 269, Elsevier BV (2020), Nr. 5, S. 4353--4380
    9. Hirche, M. ; Köhler, P. N. ; Müller, M. A. ; Allgöwer, F.: Distributed Model Predictive Control for Consensus of Constrained Heterogeneous Linear Systems. In: Proc. 59th IEEE Conf. on Decision and Control (CDC), Proc. 59th IEEE Conf. on Decision and Control (CDC). Jeju Island, Republic of Korea, 2020, S. 1248–1253
    10. Hitz, Timon ; Keim, Jens ; Munz, Claus-Dieter ; Rohde, Christian: A parabolic relaxation model for the Navier-Stokes-Korteweg equations. In: Journal of Computational Physics, Journal of Computational Physics. Bd. 421, Elsevier (2020), S. 109714
    11. Holicki, Tobias ; Scherer, Carsten W.: Output-Feedback Synthesis for a Class of Aperiodic Impulsive Systems. In: IFAC-PapersOnline, IFAC-PapersOnline. Bd. 53, 2020, S. 7299–7304
    12. Holzmüller, David ; Steinwart, Ingo: Training two-layer ReLU networks with gradient descent is inconsistent. In: arXiv:2002.04861, arXiv:2002.04861. (2020). — Published at https://jmlr.org/papers/v23/20-830.html
    13. Häufle, Daniel F. B. ; Wochner, Isabell ; Holzmüller, David ; Drieß, Danny ; Günther, Michael ; Schmitt, Syn: Muscles reduce neuronal information load : quantification of control effort in biological vs. robotic pointing and walking. In: Frontiers in Robotics and AI, Frontiers in Robotics and AI. Bd. 7, Frontiers (2020), S. 77
    14. Häufle, Daniel F. B. ; Wochner, Isabell ; Holzmüller, David ; Driess, Danny ; Günther, Michael ; Schmitt, Syn: Muscles Reduce Neuronal Information Load : Quantification of Control Effort in Biological vs. Robotic Pointing and Walking. In: Frontiers In Robotics and AI, Frontiers In Robotics and AI. Bd. 7, Frontiers Media (2020), S. 77
    15. Höge, Marvin ; Guthke, Anneli ; Nowak, Wolfgang: Bayesian Model Weighting: The Many Faces of Model Averaging. In: Water, Water. Bd. 12 (2020), Nr. 2, S. 309
  9. I

    1. Imig, Dirke ; Pollak, Nadine ; Allgöwer, Frank ; Rehm, Markus: Sample-based modeling reveals bidirectional interplay between cell cycle progression and extrinsic apoptosis. In: PLOS Computational Biology, PLOS Computational Biology. Bd. 16, Public Library of Science (2020), Nr. 6, S. 1–17
  10. K

    1. Kempter, Fabian ; Bechler, Florian ; Fehr, Jörg: Calibration Approach for Muscle Activated Human Models in Pre-Crash Maneuvers with a Driver-in-the-Loop Simulator. In: Proceedings in 6th Digital Human Modeling Symposium, Proceedings in 6th Digital Human Modeling Symposium. Skövde, Sweden, 2020
    2. Kneifl, Jonas ; Fehr, Jörg: Machine Learning Algorithms for Learning Nonlinear Terms of Reduced Mechanical Models in Explicit Structural Dynamics. In: Proceedings in Applied Mathematics and Mechanics, Proceedings in Applied Mathematics and Mechanics. (2020)
    3. Koch, A. ; Berberich, J. ; Allgöwer, F.: Verifying dissipativity properties from noise-corrupted input-state data. In: Proc. 59th IEEE Conf. on Decision and Control (CDC), Proc. 59th IEEE Conf. on Decision and Control (CDC). Jeju, South Korea, 2020, S. 616–621
    4. Koch, Timo ; Flemisch, Bernd ; Helmig, Rainer ; Wiest, Roland ; Obrist, Dominik: A multiscale subvoxel perfusion model to estimate diffusive capillary wall conductivity in multiple sclerosis lesions from perfusion MRI data. In: International Journal for Numerical Methods in Biomedical Engineering, International Journal for Numerical Methods in Biomedical Engineering. Bd. 36, Wiley (2020), Nr. 2, S. e3298
    5. Kunc, Oliver ; Fritzen, Felix: Many-scale finite strain computational homogenization via Concentric Interpolation. In: International Journal for Numerical Methods in Engineering, International Journal for Numerical Methods in Engineering. Bd. 121 (2020), Nr. 21, S. 4689--4716
    6. Kuritz, Karsten ; Stöhr, Daniela ; Maichl, Daniela Simone ; Pollak, Nadine ; Rehm, Markus ; Allgöwer, Frank: Reconstructing temporal and spatial dynamics from single-cell pseudotime using prior knowledge of real scale cell densities. In: Scientific Reports, Scientific Reports. Bd. 10, Nature Publishing Group (2020), Nr. 1, S. 3619
    7. Kurz, Marius ; Beck, Andrea: A machine learning framework for LES closure terms. In: ETNA - Electronic Transactions on Numerical Analysis, ETNA - Electronic Transactions on Numerical Analysis. (2020), S. 117–137 — ISBN 978-3-7001-8258-0
  11. L

    1. Lienstromberg, Christina ; Müller, Stefan: Local strong solutions to a quasilinear degenerate fourth-order thin-film equation. In: NoDEA Nonlinear Differential Equations Appl., NoDEA Nonlinear Differential Equations Appl. Bd. 27 (2020), Nr. 2, S. Paper No. 16, 28
  12. M

    1. Mangiagalli, M ; Carvalho, H ; Natalello, A ; Ferrario, V ; Pennati, ML ; Barbiroli, A ; Lotti, M ; Pleiss, J ; u. a.: Diverse effects of aqueous polar co-solvents on Candida antarctica lipase B. In: Int J Biol Macromol, Int J Biol Macromol. Bd. 150 (2020), S. 930–940
    2. Martin, T. ; Allgöwer, F.: Iterative data-driven inference of nonlinearity measures via successive graph approximation. In: Proc. 59th IEEE Conf. Decision and Control (CDC), Proc. 59th IEEE Conf. Decision and Control (CDC). Jeju, South Korea, 2020, S. 4760–4765
    3. Martin, T. ; Koch, A. ; Allgöwer, F.: Data-driven surrogate models for LTI systems via saddle-point dynamics. In: Proc. 21st IFAC World Congress, Proc. 21st IFAC World Congress. Berlin, Germany, 2020, S. 971–976
    4. Michalowsky, Simon ; Scherer, Carsten ; Ebenbauer, Christian: Robust and structure exploiting optimisation algorithms: An integral quadratic constraint approach. In: International Journal of Control, International Journal of Control. Bd. 2020, Taylor & Francis (2020), S. 1–24
    5. Molpeceres, G. ; Zaverkin, Viktor ; Kästner, Johannes: Neural-network assisted study of nitrogen atom dynamics on amorphous solid water – I. adsorption and desorption. In: Mon. Not. R. Astron. Soc., Mon. Not. R. Astron. Soc. Bd. 499 (2020), S. 1373–1384
    6. Munz, Tanja ; Schaefer, Noel ; Blascheck, Tanja ; Kurzhals, Kuno ; Zhang, Eugene ; Weiskopf, Daniel: Demo of a Visual Gaze Analysis System for Virtual Board Games. In: ACM Symposium on Eye Tracking Research and Applications, ACM Symposium on Eye Tracking Research and Applications. Stuttgart, Germany : Association for Computing Machinery, 2020
    7. Munz, Tanja ; Schäfer, Noel ; Blascheck, Tanja ; Kurzhals, Kuno ; Zhang, Eugene ; Weiskopf, Daniel: Comparative Visual Gaze Analysis for Virtual Board Games. In: Proceedings of the 13th International Symposium on Visual Information Communication and Interaction, Proceedings of the 13th International Symposium on Visual Information Communication and Interaction. Eindhoven, Netherlands : Association for Computing Machinery, 2020 — ISBN 9781450387507, S. 1–8
    8. Munz, Tanja ; Schäfer, Noel ; Blascheck, Tanja ; Kurzhals, Kuno ; Zhang, Eugene ; Weiskopf, Daniel: Supplemental Material for Comparative Visual Gaze Analysis for Virtual Board Games, DaRUS (2020)
    9. Müller, Philipp ; Sood, Ekta ; Bulling, Andreas: Anticipating Averted Gaze in Dyadic Interactions. In: ACM Symposium on Eye Tracking Research and Applications, ACM Symposium on Eye Tracking Research and Applications. Stuttgart, Germany : Association for Computing Machinery, 2020 — ISBN 9781450371339, S. 1–10
    10. Müller, Steffen: Symplectic Neural Networks (2020). — Bachelor Thesis, Univ. of Stuttgart
  13. N

    1. Naseri, Alireza ; Totounferoush, Amin ; González, Ignacio ; Mehl, Miriam ; Pérez-Segarra, Carlos David: A scalable framework for the partitioned solution of fluid--structure interaction problems. In: Computational Mechanics, Computational Mechanics. Bd. 66 (2020), Nr. 2, S. 471--489
    2. Nguyen, Lu Trong Khiem ; Rambausek, Matthias ; Keip, Marc-André: Variational framework for distance-minimizing method in data-driven computational mechanics. In: Computer Methods in Applied Mechanics and Engineering, Computer Methods in Applied Mechanics and Engineering. Bd. 365, Elsevier BV (2020), S. 112898
  14. O

    1. Oladyshkin, S. ; Beckers, F. ; Kroeker, I. ; Mohammadi, F. ; Heredia, A. ; Noack, M. ; Flemisch, B. ; Wieprecht, S. ; u. a.: Uncertainty quantification using Bayesian arbitrary polynomial chaos for computationally demanding environmental modelling: conventional, sparse and adaptive strategy. In: Computational Methods in Water Resources (CMWR), Computational Methods in Water Resources (CMWR), 2020
    2. Oladyshkin, Sergey ; Mohammadi, Farid ; Kroeker, Ilja ; Nowak, Wolfgang: Bayesian3 Active Learning for the Gaussian Process Emulator Using Information Theory. In: Entropy, Entropy. Bd. 22, MDPI AG (2020), Nr. 8, S. 890
    3. Oladyshkin, Sergey ; Mohammadi, Farid ; Kröker, Ilja ; Nowak, Wolfgang: Bayesian3 active learning for Gaussian process emulator using information theory. In: Entropy, Entropy. Bd. 22, Multidisciplinary Digital Publishing Institute (2020), Nr. 0890, S. 1–27
  15. P

    1. Pandey, Sandeep ; Chu, Xu ; Weigand, Bernhard ; Laurien, Eckart ; Schumacher, Jörg: Relaminarized and recovered turbulence under nonuniform body forces. In: Physical Review Fluids, Physical Review Fluids. Bd. 5, American Physical Society (APS) (2020), Nr. 10
    2. Persson, D. ; Koch, A. ; Allgöwer, F.: Probabilistic H2-norm estimation via Gaussian process system identification. In: Proc. 21st IFAC World Congress, Proc. 21st IFAC World Congress. Berlin, Germany, 2020, S. 431–436
    3. Polukhov, Elten ; Keip, Marc-André: Computational homogenization of transient chemo-mechanical processes based on a variational minimization principle. In: Advanced Modeling and Simulation in Engineering Sciences, Advanced Modeling and Simulation in Engineering Sciences. Bd. 7, Springer Science and Business Media LLC (2020), Nr. 1
    4. Praditia, Timothy ; Walser, Thilo ; Oladyshkin, Sergey ; Nowak, Wolfgang: Improving Thermochemical Energy Storage dynamics forecast with Physics-Inspired Neural Network architecture. In: Energies, Energies. Bd. 13 (2020), Nr. 15, S. 3873
  16. R

    1. Rehner, Philipp ; Gross, Joachim: Multiobjective Optimization of PCP-SAFT Parameters for Water and Alcohols Using Surface Tension Data. In: Journal of Chemical & Engineering Data, Journal of Chemical & Engineering Data. Bd. 65, American Chemical Society (ACS) (2020), Nr. 12, S. 5698--5707
    2. Reutzsch, Jonathan ; Kieffer-Roth, Corine ; Weigand, Bernhard: A consistent method for direct numerical simulation of droplet evaporation. In: Journal of Computational Physics, Journal of Computational Physics., Elsevier (2020), S. 109455
    3. Rohde, Christian ; Tang, Hao: On a stochastic Camassa--Holm type equation with higher order nonlinearities. In: Journal of Dynamics and Differential Equations, Journal of Dynamics and Differential Equations. Bd. 33, Springer (2020), S. 1823–1852
    4. Rösinger, C. A. ; Scherer, C. W.: Lifting to Passivity for $H_2$-Gain-Scheduling Synthesis with Full Block Scalings (2020)
    5. Rösinger, Christian A. ; Scherer, Carsten W.: A Flexible Synthesis Framework of Structured Controllers for Networked Systems. In: IEEE Trans. Control Netw. Syst., IEEE Trans. Control Netw. Syst. Bd. 7 (2020), Nr. 1, S. 6–18
  17. S

    1. Salm, Marie ; Barzen, Johanna ; Breitenbücher, Uwe ; Leymann, Frank ; Weder, Benjamin ; Wild, Karoline: The NISQ Analyzer: Automating the Selection of Quantum Computers for Quantum Algorithms. In: Proceedings of the 14th Symposium and Summer School on Service-Oriented Computing (SummerSOC 2020), Proceedings of the 14th Symposium and Summer School on Service-Oriented Computing (SummerSOC 2020) : Springer International Publishing, 2020, S. 66--85
    2. Salm, Marie ; Barzen, Johanna ; Leymann, Frank ; Weder, Benjamin: About a Criterion of Successfully Executing a Circuit in the NISQ Era: What $wd 1/\epsilon_eff$ Really Means. In: Proceedings of the 1st ACM SIGSOFT International Workshop on Architectures and Paradigms for Engineering Quantum Software, Proceedings of the 1st ACM SIGSOFT International Workshop on Architectures and Paradigms for Engineering Quantum Software : ACM, 2020
    3. Sarap, Chandra Shekar ; Putra, Miftahussurur Hamidi ; Fyta, Maria: Domain-size effect on the electronic properties of two-dimensional $MoS_2/WS_2$. In: Phys. Rev. B, Phys. Rev. B. Bd. 101, American Physical Society (2020), Nr. 7, S. 075129
    4. Schepp, Laura L ; Ahrens, Benedikt ; Balcewicz, Martin ; Duda, Mandy ; Nehler, Mathias ; Osorno, Maria ; Uribe, David ; Steeb, Holger ; u. a.: Digital rock physics and laboratory considerations on a high-porosity volcanic rock. In: Scientific Reports, Scientific Reports. Bd. 10, Nature Publishing Group (2020), Nr. 1, S. 1--16
    5. Schepp, Laura L. ; Ahrens, Benedikt ; Balcewicz, Martin ; Duda, Mandy ; Nehler, Mathias ; Osorno, Maria ; Uribe, David ; Steeb, Holger ; u. a.: Digital rock physics and laboratory considerations on a high-porosity volcanic rock: micro-XRCT data sets. DaRUS.
    6. Schlottke, Karin ; Reutzsch, Jonathan ; Kieffer-Roth, Corine ; Weigand, Bernhard: Direct Numerical Simulations of Evaporating Droplets at Higher Temperatures: Application of a Consistent Numerical Approach. In: Droplet Interactions and Spray Processes, Droplet Interactions and Spray Processes : Springer International Publishing, 2020, S. 287–299
    7. Schneider, Martin ; Weishaupt, Kilian ; Gläser, Dennis ; Boon, Wietse M ; Helmig, Rainer: Coupling staggered-grid and MPFA finite volume methods for free flow/porous-medium flow problems. In: Journal of Computational Physics, Journal of Computational Physics. Bd. 401, Elsevier (2020), S. 109012
    8. Schäfer Rodrigues Silva, A. ; Guthke, A. ; Höge, M. ; Cirpka, O.A. ; Nowak, W.: Strategies for simplifying reactive transport models - a Bayesian model comparison. In: Water Resources Research, Water Resources Research. Bd. 56 (2020), S. e2020WR028100
    9. Sinsbeck, M. ; Höge, M. ; Nowak, W.: Exploratory-phase-free estimation of GP hyperparameters in sequential design methods - at the example of Bayesian inverse problems. In: Frontiers in Artificial Intelligence, section AI in Food, Agriculture and Water, Frontiers in Artificial Intelligence, section AI in Food, Agriculture and Water. Bd. 3 (2020), Nr. 52, S. 1–16
    10. Sivaraman, Ganesh ; Krishnamoorthy, Anand Narayanan ; Baur, Matthias ; Holm, Christian ; Stan, Marius ; Csányi, Gábor ; Benmore, Chris ; Vázquez-Mayagoitia, Álvaro: Machine-learned interatomic potentials by active learning: amorphous and liquid hafnium dioxide. In: npj Computational Materials, npj Computational Materials. Bd. 6, Springer Science and Business Media LLC (2020), Nr. 1
    11. Sood, Ekta ; Tannert, Simon ; Frassinelli, Diego ; Bulling, Andreas ; Vu, Ngoc Thang: Interpreting Attention Models with Human Visual Attention in Machine Reading Comprehension. In: Proceedings of the 24th Conference on Computational Natural Language Learning, Proceedings of the 24th Conference on Computational Natural Language Learning. Online : Association for Computational Linguistics, 2020, S. 12--25
    12. Sood, Ekta ; Tannert, Simon ; Mueller, Philipp ; Bulling, Andreas: Improving Natural Language Processing Tasks with Human Gaze-Guided Neural Attention. In: Larochelle, H. ; Ranzato, M. ; Hadsell, R. ; Balcan, M. F. ; Lin, H. (Hrsg.) ; Larochelle, H. ; Ranzato, M. ; Hadsell, R. ; Balcan, M. F. ; Lin, H. (Hrsg.): Advances in Neural Information Processing Systems, Advances in Neural Information Processing Systems. Bd. 33 : Curran Associates, Inc., 2020, S. 6327--6341
    13. Stockinger, P ; Roth, S ; Müller, M ; Pleiss, J: Systematic evaluation of imine-reducing enzymes: Common principles in imine reductases, β-hydroxyacid dehydrogenases, and short-chain dehydrogenases/reductases. In: ChemBioChem, ChemBioChem. (2020)
    14. Stöhr, Daniela ; Jeltsch, Albert ; Rehm, Markus: TRAIL receptor signaling: From the basics of canonical signal transduction toward its entanglement with ER stress and the unfolded protein response. In: Cell Death Regulation in Health and Disease-Part A, Cell Death Regulation in Health and Disease-Part A., Academic Press (2020), S. 57
    15. Stöhr, Daniela ; Rehm, Markus: Linking hyperosmotic stress and apoptotic sensitivity. In: The FEBS Journal, The FEBS Journal., Blackwell Publishing Ltd (2020), S. febs.15520
    16. Stöhr, Daniela ; Schmid, Jens O. ; Beigl, Tobias B. ; Mack, Alexandra ; Maichl, Daniela S. ; Cao, Kai ; Budai, Beate ; Fullstone, Gavin ; u. a.: Stress-induced TRAILR2 expression overcomes TRAIL resistance in cancer cell spheroids. In: Cell Death & Differentiation, Cell Death & Differentiation. (2020), Nr. 27, S. 3037–3052
  18. T

    1. Tomalka, André ; Weidner, Sven ; Hahn, Daniel ; Seiberl, Wolfgang ; Siebert, Tobias: Cross-Bridges and Sarcomeric Non-cross-bridge Structures Contribute to Increased Work in Stretch-Shortening Cycles. In: Siebert, T. (Hrsg.) Frontiers in Physiology, Frontiers in Physiology. Bd. 11, Frontiers Media SA (2020)
    2. Tovey, Samuel ; Narayanan Krishnamoorthy, Anand ; Sivaraman, Ganesh ; Guo, Jicheng ; Benmore, Chris ; Heuer, Andreas ; Holm, Christian: DFT accurate interatomic potential for molten NaCl from machine learning. In: The Journal of Physical Chemistry C, The Journal of Physical Chemistry C. Bd. 124, ACS Publications (2020), Nr. 47, S. 25760–25768
  19. V

    1. Vetma, Vesna ; Guttà, Cristiano ; Peters, Nathalie ; Praetorius, Christian ; Hutt, Meike ; Seifert, Oliver ; Meier, Friedegund ; Kontermann, Roland ; u. a.: Convergence of pathway analysis and pattern recognition predicts sensitization to latest generation TRAIL therapeutics by IAP antagonism. In: Cell Death & Differentiation, Cell Death & Differentiation. Bd. 27, Springer Science and Business Media LLC (2020), Nr. 8, S. 2417--2432
  20. W

    1. Weder, B. ; Breitenbücher, U. ; Leymann, F. ; Wild, K.: Integrating Quantum Computing into Workflow Modeling and Execution. In: 2020 IEEE/ACM 13th International Conference on Utility and Cloud Computing (UCC), 2020 IEEE/ACM 13th International Conference on Utility and Cloud Computing (UCC), 2020, S. 279–291
    2. Weder, Benjamin ; Barzen, Johanna ; Leymann, Frank ; Salm, Marie ; Vietz, Daniel: The Quantum Software Lifecycle. In: Proceedings of the 1st ACM SIGSOFT International Workshop on Architectures and Paradigms for Engineering Quantum Software (APEQS 2020), Proceedings of the 1st ACM SIGSOFT International Workshop on Architectures and Paradigms for Engineering Quantum Software (APEQS 2020) : ACM, 2020, S. 2--9
    3. Weder, Benjamin ; Breitenbücher, Uwe ; Képes, Kálmán ; Leymann, Frank ; Zimmermann, Michael: Deployable Self-Contained Workflow Models. In: Proceedings of the 8th European Conference on Service-Oriented and Cloud Computing (ESOCC 2020), Proceedings of the 8th European Conference on Service-Oriented and Cloud Computing (ESOCC 2020) : Springer International Publishing, 2020, S. 85--96
    4. Weishaupt, Kilian ; Class, Holger ; Coltman, Edward ; Emmert, Simon ; Flemisch, Bernd ; Gläser, Dennis ; Grüninger, Christoph ; Heck, Katharina ; u. a.: DuMux 3.3.0, Zenodo (2020)
    5. Wild, Karoline ; Breitenbücher, Uwe ; Képes, Kálmán ; Leymann, Frank ; Weder, Benjamin: Decentralized Cross-Organizational Application Deployment Automation: An Approach for Generating Deployment Choreographies Based on Declarative Deployment Models. In: Proceedings of the 32nd Conference on Advanced Information Systems Engineering (CAiSE 2020), Proceedings of the 32nd Conference on Advanced Information Systems Engineering (CAiSE 2020). Bd. 12127 : Springer International Publishing, 2020, S. 20--35
    6. Wochner, Isabell ; Driess, Danny ; Zimmermann, Heiko ; Haeufle, Daniel FB ; Toussaint, Marc ; Schmitt, Syn: Optimality principles in human point-to-manifold reaching accounting for muscle dynamics. In: Frontiers in Computational Neuroscience, Frontiers in Computational Neuroscience. Bd. 14, Frontiers (2020), S. 38
  21. X

    1. Xiao, S. ; Oladyshkin, S. ; Nowak, W.: Forward-reverse switch between density-based and regional sensitivity analysis. In: Applied Mathematical Modelling, Applied Mathematical Modelling. Bd. 84 (2020), S. 377–392
    2. Xiao, Sinan ; Oladyshkin, Sergey ; Nowak, Wolfgang: Reliability analysis with stratified importance sampling based on adaptive Kriging. In: Reliability Engineering & System Safety, Reliability Engineering & System Safety. Bd. 197, Elsevier BV (2020), S. 106852
    3. Xu, Teng ; Reuschen, Sebastian ; Nowak, Wolfgang ; Franssen, Harrie-Jan Hendricks: Preconditioned Crank-Nicolson Markov chain Monte Carlo coupled with parallel tempering: An efficient method for Bayesian inversion of multi-Gaussian log-hydraulic conductivity fields. In: Water Resources Research, Water Resources Research. Bd. 56 (2020), Nr. 8, S. e2020WR027110
    4. Xu, Xinmeng ; Range, Jan ; Gygli, Gudrun ; Pleiss, Jürgen: Analysis of Thermophysical Properties of Deep Eutectic Solvents by Data Integration. In: Journal of Chemical & Engineering Data, Journal of Chemical & Engineering Data. Bd. 65 (2020), S. 1172–1179
  22. Y

    1. Yang, Guang (杨光) ; Chu, Xu (初旭) ; Vaikuntanathan, Visakh ; Wang, Shanshan (王珊珊) ; Wu, Jingyi (吴静怡) ; Weigand, Bernhard ; Terzis, Alexandros: Droplet mobilization at the walls of a microfluidic channel. In: Physics of Fluids, Physics of Fluids. Bd. 32 (2020), Nr. 1, S. 012004
    2. Yu, Xingyao ; Angerbauer, Katrin ; Mohr, Peter ; Kalkofen, Denis ; Sedlmair, Michael: Perspective Matters: Design Implications for Motion Guidance in Mixed Reality. In: Proceedings of the IEEE International Symposium on Mixed and Augmented Reality (ISMAR), Proceedings of the IEEE International Symposium on Mixed and Augmented Reality (ISMAR), 2020
  23. Z

    1. Zaverkin, V. ; Kästner, J.: Gaussian Moments as Physically Inspired Molecular Descriptors for Accurate and Scalable Machine Learning Potentials. In: J. Chem. Theory Comput., J. Chem. Theory Comput. Bd. 16 (2020), S. 5410–5421
    2. Zeman, Johannes ; Kondrat, Svyatoslav ; Holm, Christian: Bulk ionic screening lengths from extremely large-scale molecular dynamics simulations. In: Chem. Commun., Chem. Commun. Bd. 56, The Royal Society of Chemistry (2020), Nr. 100, S. 15635–15638
    3. Zimmermann, M. ; Breitenbücher, U. ; Képes, K. ; Leymann, F. ; Weder, B.: Data Flow Dependent Component Placement of Data Processing Cloud Applications. In: 2020 IEEE International Conference on Cloud Engineering (IC2E), 2020 IEEE International Conference on Cloud Engineering (IC2E), 2020, S. 83–94
To the top of the page