2017

  1. (

    1. E. R. C. (ERC), Ed., “Guidelines on Implementation of Open Access to Scientific Publications and Research Data in projects supported by the European Research Council under Horizon 2020.” 2017, [Online]. Available: http://ec.europa.eu/research/participants/data/ref/h2020/other/hi/oa-pilot/h2020-hi-erc-oa-guide_en.pdf.
    2. E. U. A. (EUA), Ed., “Towards Open Access  to Research  Data Aims and recommendations for university  leaders and National Rectors’ Conferences  on Research Data Management and Text  and Data Mining.” 2017, [Online]. Available: http://www.eua.be/Libraries/publications-homepage-list/towards-open-access-to-research-data.pdf?sfvrsn=4.
  2. A

    1. B. Afkham and J. Hesthaven, “Structure Preserving Model Reduction of Parametric Hamiltonian Systems,” SIAM Journal on Scientific Computing, vol. 39, no. 6, pp. A2616–A2644, 2017, doi: 10.1137/17M1111991.
    2. SS. Agada, S. Geiger, A. ElSheikh, and S. Oladyshkin, “Data-driven surrogates for rapid simulation and optimization of WAG injection in fractured carbonate reservoirs,” Petroleum Geoscience, vol. 23, pp. 270--283, 2017, doi: 10.1144/petgeo2016-068.
    3. M. Alkämper and R. Klöfkorn, “Distributed Newest Vertex Bisection,” Journal of Parallel and Distributed Computing, vol. 104, pp. 1–11, 2017, doi: http://dx.doi.org/10.1016/j.jpdc.2016.12.003.
    4. M. Alkämper, R. Klöfkorn, and F. Gaspoz, “A Weak Compatibility Condition for Newest Vertex Bisection in any  Dimension,” 2017.
    5. M. Alkämper and A. Langer, “Using DUNE-ACFem for Non-smooth Minimization of Bounded Variation  Functions,” Archive of Numerical Software, vol. 5, no. 1, pp. 3--19, 2017, [Online]. Available: https://journals.ub.uni-heidelberg.de/index.php/ans/article/view/27475.
    6. M. Alk�mper and R. Klofkorn, “Distributed Newest Vertex Bisection,” JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING, vol. 104, pp. 1–11, 2017, doi: 10.1016/j.jpdc.2016.12.003.
    7. A. Alla, B. Haasdonk, and A. Schmidt, “Feedback control of parametrized PDEs via model order reduction and  dynamic programming principle,” University of Stuttgart, 2017. [Online]. Available: http://www.simtech.uni-stuttgart.de/publikationen/prints.php?ID=1765.
    8. A. Alla, A. Schmidt, and B. Haasdonk, Model Order Reduction Approaches for Infinite Horizon Optimal Control Problems via the HJB Equation. Springer International Publishing, 2017.
    9. A. Alla, A. Schmidt, and B. Haasdonk, Model Order Reduction Approaches for Infinite Horizon Optimal Control Problems via the HJB Equation. Springer International Publishing, 2017.
    10. A. Allen et al., “Engineering Academic Software (Dagstuhl Perspectives Workshop 16252).,” Dagstuhl Manifestos, vol. 6, no. 1, pp. 1–20, 2017, [Online]. Available: http://dblp.uni-trier.de/db/journals/dagstuhl-manifestos/dagstuhl-manifestos6.html#AllenABCCCCCGGG17.
    11. A. Armiti-Juber and C. Rohde, “On Darcy-and Brinkman-Type Models for Two-Phase Flow in Asymptotically  Flat Domains,” 2017, [Online]. Available: https://arxiv.org/abs/1712.07470.
    12. M. Atkinson, S. Gesing, J. Montagnat, and I. Taylor, “Scientific workflows: Past, present and future,” Future Generation Computer Systems, vol. 75, pp. 216–227, 2017, doi: https://doi.org/10.1016/j.future.2017.05.041.
  3. B

    1. A. Barth and A. Stein, “Approximation and simulation of infinite-dimensional Levy processes,” Stochastic and Partial Differential Equations, 2017, doi: 10.1007/s40072-017-0109-2.
    2. A. Barth and F. G. Fuchs, “Uncertainty quantification for linear hyperbolic equations  with stochastic process or random field coefficients,” Appl. Numer. Math., vol. 121, pp. 38--51, 2017, doi: 10.1016/j.apnum.2017.06.009.
    3. A. Barth, B. Harrach, N. Hyvoenen, and L. Mustonen, “Detecting stochastic inclusions in electrical impedance tomography,” INVERSE PROBLEMS, vol. 33, no. 11, 2017, doi: 10.1088/1361-6420/aa8f5c.
    4. A. Barth and A. Stein, “A study of elliptic partial differential equations with jump diffusion  coefficients,” 2017.
    5. A. Barth, B. Harrach, N. Hyvönen, and L. Mustonen, “Detecting stochastic inclusions in electrical impedance tomography,” Inv. Prob., vol. 33, no. 11, p. 115012, 2017, [Online]. Available: http://arxiv.org/abs/1706.03962.
    6. B. Baumann, D. Hamann, and P. Eberhard, “Time-dependent Parametric Model Order Reduction for Material-Removal Simulations,” Modeling, Simulation and Applications, vol. 17, 2017, doi: 10.1007/978-3-319-58786-8_30.
    7. B. Baumann, D. Hamann, and P. Eberhard, “Time-dependent Parametric Model Order Reduction for Material-Removal Simulations,” Modeling, Simulation and Applications, vol. 17, 2017, doi: 10.1007/978-3-319-58786-8_30.
    8. P. U. Baur, “Comparison of methods for parametric model order reduction of instationary problem,” Chapter in P. Benner, A. Cohen, M. Ohlberger, K. Willcox (Eds.): Model Reduction and Approximation: Theory and Algorithms, pp. 377--407, 2017, doi: 10.1137/1.9781611974829.ch9.
    9. A. Bayer, S. Schmitt, M. Günther, and D. Haeufle, “The influence of biophysical muscle properties on simulating fast human arm movements,” Computer Methods in Biomechanics and Biomedical Engineering, vol. 20, no. 8, pp. 803--821, 2017.
    10. F. Beck, M. Burch, S. Diehl, and D. Weiskopf, “A Taxonomy and Survey of Dynamic Graph Visualization,” Computer Graphics Forum, vol. 36, no. 1, pp. 133--159, 2017, doi: 10.1111/cgf.12791.
    11. B. Becker, B. Guo, K. Bandilla, M. A. Celia, B. Flemisch, and R. Helmig, “A Pseudo-Vertical Equilibrium Model for Slow Gravity Drainage Dynamics,” Water Resources Research, vol. 53, no. 12, pp. 10491--10507, 2017, doi: 10.1002/2017WR021644.
    12. A. Bhatt and R. VanGorder, “Chaos in a non-autonomous nonlinear system describing asymmetric  water wheels,” 2017.
    13. A. Bhatt and B. E. Moore, “Structure-preserving ERK methods for non-autonomous DEs.” 2017.
    14. A. Bhatt and B. E. Moore, “Structure-preserving numerical integration of DEs with conformal  invariants.” 2017.
    15. C. Bradley et al., “Towards realistic HPC models of the neuromuscular system,” Frontiers in Physiology, 2017, [Online]. Available: http://www.simtech.uni-stuttgart.de/publikationen/prints.php?ID=1772.
    16. M. Brehler, M. Schirwon, D. Göddeke, and P. M. Krummrich, “A GPU-accelerated Fourth-Order Runge-Kutta in the Interaction Picture Method for the Simulation of Nonlinear Signal Propagation in Multimode Fibers,” Journal of Lightwave Technology, vol. 35, pp. 3622--3628, 2017, doi: 10.1109/JLT.2017.2715358.
    17. M. Brehler, M. Schirwon, D. Göddeke, and P. M. Krummrich, “A GPU-accelerated Fourth-Order Runge-Kutta in the Interaction  Picture Method for the Simulation of Nonlinear Signal Propagation  in Multimode Fibers,” Journal of Lightwave Technology, vol. 35, no. 17, pp. 3622--3628, 2017, doi: 10.1109/JLT.2017.2715358.
    18. N. Brown et al., “Weekly Time Course of Neuro-Muscular Adaptation to Intensive Strength Training,” Frontiers in Physiology, vol. 8, p. 329, 2017, doi: 10.3389/fphys.2017.00329.
    19. V. Bruder, S. Frey, and T. Ertl, “Prediction-Based Load Balancing and Resolution Tuning for Interactive Volume Raycasting,” Visual Informatics, 2017, doi: 10.1016/j.visinf.2017.09.001.
    20. F. D. Brunner, W. P. M. H. Heemels, and F. Allgöwer, “Robust Event-triggered MPC With Guaranteed Asymptotic Bound and Average Sampling Rate,” IEEE Transactions on Automatic Control, 2017, doi: 10.1109/TAC.2017.2702646.
    21. F. D. Brunner, W. P. M. H. Heemels, and F. Allgöwer, “Robust Event-triggered MPC With Guaranteed Asymptotic Bound and Average Sampling Rate,” IEEE Transactions on Automatic Control, 2017, doi: 10.1109/TAC.2017.2702646.
    22. T. Brünnette, G. Santin, and B. Haasdonk, “Greedy kernel methods for accelerating implicit integrators for parametric ODEs,” Numerical Mathematics and Advanced Applications - ENUMATH 2017, 2017, [Online]. Available: http://www.simtech.uni-stuttgart.de/publikationen/prints.php?ID=1767.
    23. M. Bußler et al., “Visualization of fracture progression in peridynamics,” Computers & Graphics, vol. 67, pp. 45--57, 2017, doi: 10.1016/j.cag.2017.05.003.
    24. L. Böger, M.-A. Keip, and C. Miehe, “Minimization and Saddle-Point Principles for the Phase-Field Modeling of Fracture in Hydrogels,” Computational Materials Science, vol. 138, pp. 474--485, 2017, doi: 10.1016/j.commatsci.2017.06.010.
    25. R. Bürger and I. Kröker, “Hybrid Stochastic Galerkin Finite Volumes for the Diffusively Corrected Lighthill-Whitham-Richards Traffic Model,” Springer Proceedings in Mathematics & Statistics, vol. 200, pp. 189--197, 2017, doi: 10.1007/978-3-319-57394-6_21.
    26. R. Bürger and I. Kröker, “Hybrid Stochastic Galerkin Finite Volumes for the Diffusively Corrected Lighthill-Whitham-Richards Traffic Model,” Springer Proceedings in Mathematics & Statistics, vol. 200, pp. 189--197, 2017, doi: 10.1007/978-3-319-57394-6_21.
    27. R. Bürger and I. Kröker, “Hybrid Stochastic Galerkin Finite Volumes for the Diffusively Corrected  Lighthill-Whitham-Richards Traffic Model,” in Finite Volumes for Complex Applications VIII - Hyperbolic, Elliptic  and Parabolic Problems: FVCA 8, Lille, France, June 2017, C. Cancès and P. Omnes, Eds. Cham: Springer International Publishing, 2017, pp. 189--197.
  4. C

    1. B. W. Carabelli, R. Blind, F. Dürr, and K. Rothermel, “State-dependent priority scheduling for networked control systems,” Proceedings of the American Control Conference (ACC), pp. 1003--1010, 2017, doi: 10.23919/ACC.2017.7963084.
    2. R. Cavoretto, S. De Marchi, A. De Rossi, E. Perracchione, and G. Santin, “Partition of unity interpolation using stable kernel-based techniques,” APPLIED NUMERICAL MATHEMATICS, vol. 116, no. SI, pp. 95–107, 2017, doi: 10.1016/j.apnum.2016.07.005.
    3. C. Chalons, C. Rohde, and M. Wiebe, “A Finite Volume Method for Undercompressive Shock Waves in Two Space Dimensions,” ESAIM Math. Model. Numer. Anal., 2017, [Online]. Available: https://www.esaim-m2an.org/component/article?access=doi&doi=10.1051/m2an/2017027.
    4. C. Chalons, J. Magiera, C. Rohde, and M. Wiebe, “A Finite-Volume Tracking Scheme for Two-Phase Compressible Flow,” Springer Proc. Math. Stat., 2017, [Online]. Available: http://www.simtech.uni-stuttgart.de/publikationen/prints.php?ID=1721.
    5. F. Charette and P. Kime, “biblatex-cheatsheet – BibLaTeX/Biber ‘cheat sheet.’” 2017, [Online]. Available: https://ctan.org/pkg/biblatex-cheatsheet.
    6. A. Chertock, P. Degond, and J. Neusser, “An asymptotic-preserving method for a relaxation of the    Navier-Stokes-Korteweg equations,” JOURNAL OF COMPUTATIONAL PHYSICS, vol. 335, pp. 387–403, 2017, doi: 10.1016/j.jcp.2017.01.030.
    7. B. R. Childers and P. K. Chrysanthis, “Artifact Evaluation: Is It a Real Incentive?,” in 2017 IEEE 13th International Conference on e-Science (e-Science), 2017, pp. 488–489, doi: 10.1109/eScience.2017.79.
    8. K. B. Christensen, M. Günther, S. Schmitt, and T. Siebert, “Strain in shock-loaded skeletal muscle and the time scale of muscular wobbling mass dynamics,” Scientific Reports, vol. 7, no. 1, p. 13266, 2017, [Online]. Available: https://doi.org/10.1038/s41598-017-13630-7.
    9. S. Copplestone, P. Ortwein, and C.-D. Munz, “Complex-Frequency Shifted PMLs for Maxwell"s Equations With Hyperbolic Divergence Cleaning and Their Application in Particle-in-Cell Codes,” IEEE Transactions on Plasma Science, vol. 45, pp. 2--14, 2017, doi: 10.1109/TPS.2016.2637061.
  5. D

    1. R. F. da Silva, R. Filgueira, I. Pietri, M. Jiang, R. Sakellariou, and E. Deelman, “A characterization of workflow management systems for extreme-scale applications,” Future Generation Computer Systems, vol. 75, pp. 228–238, 2017, doi: https://doi.org/10.1016/j.future.2017.02.026.
    2. L. Danish, D. Stöhr, P. Scheurich, and N. Pollak, “TRAIL-R3/R4 and Inhibition of TRAIL Signalling in Cancer,” in TRAIL, Fas Ligand, TNF and TLR3 in Cancer, O. Micheau, Ed. Cham: Springer International Publishing, 2017, pp. 27--57.
    3. S. De Marchi, A. Iske, and G. Santin, “Image Reconstruction from Scattered Radon Data by Weighted Positive  Definite Kernel Functions,” 2017.
    4. S. De Marchi, A. Idda, and G. Santin, “A Rescaled Method for RBF Approximation,” in Approximation Theory XV: San Antonio 2016, G. E. Fasshauer and L. L. Schumaker, Eds. Cham: Springer International Publishing, 2017, pp. 39--59.
    5. DFG, “Replizierbarkeit von Forschungsergebnissen Eine Stellungnahme der Deutschen Forschungsgemeinschaft,” Deutsche Forschungsgemeinschaft, Stellungnahme, 2017. [Online]. Available: http://www.dfg.de/download/pdf/dfg_im_profil/reden_stellungnahmen/2017/170425_stellungnahme_replizierbarkeit_forschungsergebnisse_de.pdf.
    6. V. Dhillon, D. Metcalf, and M. Hooper, Blockchain Enabled Applications. Berkeley, CA: Apress, 2017.
    7. C. Dibak, F. Dürr, and K. Rothermel, “Demo: Server-assisted interactive mobile simulations for pervasive applications,” Proceesings of the 15th IEEE International Conference on Pervasive Computing and Communications Workshops, 2017, doi: 10.1109/PERCOMW.2017.7917525.
    8. C. Dibak, A. Schmidt, F. Dürr, B. Haasdonk, and K. Rothermel, “Server-Assisted Interactive Mobile Simulations for Pervasive Applications,” Proceesings of the 15th IEEE International Conference on Pervasive Computing and Communications, 2017, doi: 10.1109/PERCOM.2017.7917857.
    9. C. Dibak, A. Schmidt, F. Dürr, B. Haasdonk, and K. Rothermel, “Server-Assisted Interactive Mobile Simulations for Pervasive Applications,” Proceesings of the 15th IEEE International Conference on Pervasive Computing and Communications, 2017, doi: 10.1109/PERCOM.2017.7917857.
    10. C. Dibak, A. Schmidt, F. Dürr, B. Haasdonk, and K. Rothermel, “Server-Assisted Interactive Mobile Simulations for Pervasive Applications,” in Proceedings of the 15th IEEE International Conference on Pervasive  Computing and Communications (PerCom), Kona, Hawaii, USA, 2017, pp. 1--10, [Online]. Available: http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2017-02&engl=1.
    11. D. Drescher, Blockchain Basics. Berkeley, CA: Apress, 2017.
    12. W.-P. Düll, B. Hilder, and G. Schneider, “Analysis of the embedded cell method in 1D for the numerical homogenization of metal-ceramic composite materials.,” J. Appl. Anal., 2017, [Online]. Available: http://www.simtech.uni-stuttgart.de/publikationen/prints.php?ID=1671.
    13. W.-P. Düll, B. Hilder, and G. Schneider, “Analysis of the embedded cell method in 2D for the numerical homogenization of metal-ceramic composite materials.,” European J. Appl. Math., 2017, [Online]. Available: http://www.simtech.uni-stuttgart.de/publikationen/prints.php?ID=1670.
  6. E

    1. H. Ebel, E. Sharafian Ardakani, and P. Eberhard, “Distributed Model Predictive Formation Control with Discretization-Free Path Planning for Transporting a Load. Robotics and Autonomous Systems,” Robotics and Autonomous Systems, vol. 96, pp. 211--223, 2017, doi: 10.1016/j.robot.2017.07.007.
    2. H. Ebel, E. Sharafian Ardakani, and P. Eberhard, “Comparison of Distributed Model Predictive Control Approaches for Transporting a Load by a Formation of Mobile Robots,” Proceedings of the 8th ECCOMAS Thematic Conference on Multibody Dynamics, 2017, [Online]. Available: http://www.simtech.uni-stuttgart.de/publikationen/prints.php?ID=1717.
    3. H. Ebel, E. Sharafian Ardakani, and P. Eberhard, “Distributed Model Predictive Formation Control with Discretization-Free Path Planning for Transporting a Load. Robotics and Autonomous Systems,” Robotics and Autonomous Systems, vol. 96, pp. 211--223, 2017, doi: 10.1016/j.robot.2017.07.007.
    4. W. Ehlers and C. Luo, “A phase-field approach embedded in the Theory of Porous Media for the description of dynamic hydraulic fracturing,” Computer Methods in Applied Mechanics and Engineering, vol. 315, pp. 348--368, 2017, doi: 10.1016/j.cma.2016.10.045.
    5. W. Ehlers and C. Luo, “A phase-field approach embedded in the Theory of Porous Media for the description of dynamic hydraulic fracturing,” Computer Methods in Applied Mechanics and Engineering, vol. 315, pp. 348--368, 2017, doi: 10.1016/j.cma.2016.10.045.
    6. J. Einbock, “Informationsbeschaffungs- und Publikationsverhalten von Wissenschaftlerinnen und Wissenschaftlern der natur- und ingenieurwissenschaftlichen Fächer,” 2017.
    7. M. P. Englert, “Learning Manipulation Skills from a Single Demonstration,” International Journal of Robotics Research, 2017, [Online]. Available: https://ipvs.informatik.uni-stuttgart.de/mlr/papers/17-englert-IJRRa.pdf.
  7. F

    1. S. Fechter, C.-D. Munz, C. Rohde, and C. Zeiler, “A sharp interface method for compressible liquid-vapor flow with phase transition and surface tension,” Journal of Computational Physics, vol. 336, pp. 347--374, 2017, [Online]. Available: https://doi.org/10.1016/j.jcp.2017.02.001.
    2. S. Fechter, C.-D. Munz, C. Rohde, and C. Zeiler, “Approximate Riemann solver for compressible liquid vapor flow with phase transition and surface tension,” Computers & Fluids, 2017, [Online]. Available: https://doi.org/10.1016/j.compfluid.2017.03.026.
    3. J. Fehr, D. Grunert, A. Bhatt, and B. Hassdonk, “A Sensitivity Study of Error Estimation in Reduced Elastic Multibody  Systems,” in Proceedings of MATHMOD 2018, Vienna, Austria, 2017.
    4. J. Fehr and C. Kleinbach, “Optimal Deceleration of Surrogate Models in a Generic Side Impact Setup. International Journal of Crashworthiness,” International Journal of Crashworthiness, 2017, doi: 10.1080/13588265.2017.1287525.
    5. J. Fehr, F. Kempter, C. Kleinbach, and S. Schmitt, “Guiding strategy for an open source Hill-type muscle model in LS-DYNA and implementation in the upper extremity of a HBM,” in Proceedings of the IRCOBI conference, Antwerp, Belgium, 2017.
    6. M. Feistauer, O. Bartos, F. Roskovec, and A.-M. S�ndig, “Analysis of the FEM and DGM for an elliptic problem with a nonlinear  Newton boundary condition,” Proceeding of the EQUADIFF 17, pp. 127–136, 2017, [Online]. Available: http://www.iam.fmph.uniba.sk/amuc/ojs/index.php/equadiff/.
    7. M. Feistauer, F. Roskovec, and A.-M. S�ndig, “Discontinuous Galerkin Method for an Elliptic Problem with Nonlinear  Boundary Conditions in a Polygon,” IMA, vol. 00, pp. 1–31, 2017, doi: https://doi.org/10.1093/imanum/drx070.
    8. O. Fernandes, S. Frey, and T. Ertl, “Transportation-based Visualization of Energy Conversion,” IVAPP, p. 12, 2017, [Online]. Available: http://www.simtech.uni-stuttgart.de/publikationen/prints.php?ID=1537.
    9. M. Fetzer and C. W. Scherer, “Absolute stability analysis of discrete time feedback interconnections,” 20th IFAC World Congres, 2017, [Online]. Available: http://www.mathematik.uni-stuttgart.de/fak8/imng/lehrstuhl/lehrstuhl_fuer_mathematische_systemtheorie/publikationen/papers/FetSch17.pdf.
    10. M. Fetzer and C. W. Scherer, “Full-block multipliers for repeated, slope restricted scalar nonlinearities,” Int. J. Robust Nonlin., 2017, doi: 10.1002/rnc.3751.
    11. M. Fetzer and C. W. Scherer, “Zames-Falb Multipliers for Invariance,” tIEEE Control Systems Letters, vol. 99, 2017, doi: 10.1109/LCSYS.2017.2718556.
    12. M. Fetzer, C. W. Scherer, and J. Veenman, “Invariance with Dynamic Multipliers,” IEE T. Automat. Contr., 2017, doi: 10.1109/TAC.2017.2762764.
    13. M. Fetzer and C. W. Scherer, “Zames-Falb Multipliers for Invariance,” tIEEE Control Systems Letters, vol. 99, 2017, doi: 10.1109/LCSYS.2017.2718556.
    14. M. Fetzer, C. W. Scherer, and J. Veenman, “Invariance with Dynamic Multipliers,” IEE T. Automat. Contr., 2017, doi: 10.1109/TAC.2017.2762764.
    15. M. Fetzer, “From classical absolute stability tests towards a comprehensive robustness analysis,” Dissertation, Stuttgart, 2017.
    16. T. Fetzer, C. Grüninger, B. Flemisch, and R. Helmig, “On the Conditions for Coupling Free Flow and Porous-Medium Flow in a Finite Volume Framework,” Finite Volumes for Complex Applications VIII, pp. 347--356, 2017, doi: 10.1007/978-3-319-57394-6_37.
    17. S. Fischer and I. Steinwart, Sobolev Norm Learning Rates for Regularized Least-Squares Algorithm. 2017.
    18. S. Frey, “Sampling and Estimation of Pairwise Similarity in Spatio-Temporal Data Based on Neural Networks,” Informatics, 2017, doi: 10.3390/informatics4030027.
    19. S. Frey and T. Ertl, “Fast Flow-based Distance Quantification and Interpolation for High-Resolution Density Distributions,” EuroGraphics 2017, Short Paper, 2017, doi: 10.2312/egsh.20171009.
    20. S. Frey and T. Ertl, “Progressive Direct Volume-to-Volume Transformation,” IEEE Transactions on Visualization and Computer Graphics, vol. 23, pp. 921--930, 2017, doi: 10.1109/TVCG.2016.2599042.
    21. S. Frey and T. Ertl, “Progressive Direct Volume-to-Volume Transformation,” IEEE Transactions on Visualization and Computer Graphics, vol. 23, pp. 921--930, 2017, doi: 10.1109/TVCG.2016.2599042.
    22. F. Fritzen and M. Hassani, “Space-time model order reduction for nonlinear viscoelastic systems subjected to long-term loading,” Meccanica, vol. 52, no. 276, pp. 1--23, 2017, doi: 10.1007/s11012-017-0734-x.
    23. S. Funke, T. Mendel, A. Miller, S. Storandt, and M. Wiebe, “Map Simplification with Topology Constraints: Exactly and in Practice,” in Proceedings of the Ninteenth Workshop on Algorithm Engineering and  Experiments, ALENEX 2017, Barcelona, Spain, Hotel Porta Fira, January  17-18, 2017., 2017, pp. 185--196, doi: 10.1137/1.9781611974768.15.
  8. G

    1. F. D. Gaspoz, C. Kreuzer, K. Siebert, and D. Ziegler, “A convergent time-space adaptive $dG(s)$ finite element method for  parabolic problems motivated by equal error distribution,” Submitted, 2017.
    2. F. D. Gaspoz, P. Morin, and A. Veeser, “A posteriori error estimates with point sources in fractional sobolev  spaces,” Numerical Methods for Partial Differential Equations, vol. 33, no. 4, pp. 1018--1042, 2017, doi: 10.1002/num.22065.
    3. F. D. Gaspoz and P. Morin, “APPROXIMATION CLASSES FOR ADAPTIVE HIGHER ORDER FINITE ELEMENT    APPROXIMATION (vol 83, pg 2127, 2014),” MATHEMATICS OF COMPUTATION, vol. 86, no. 305, pp. 1525–1526, 2017, doi: 10.1090/mcom/3243.
    4. A. Gholami, A. Mang, K. Scheufele, C. Davatzikos, M. Mehl, and G. Biros, “A Framework for Scalable Biophysics-based Image Analysis,” Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis SC17, pp. 19:1--19:13, 2017, doi: 10.1145/3126908.3126930.
    5. J. Giesselmann and T. Pryer, “Goal-oriented error analysis of a DG scheme for a second gradient  elastodynamics model,” in Finite Volumes for Complex Applications VIII-Methods and Theoretical  Aspects, 2017, vol. 199, [Online]. Available: http://www.springer.com/de/book/9783319573960.
    6. J. Giesselmann and A. E. Tzavaras, “Stability properties of the Euler-Korteweg system with nonmonotone  pressures,” Appl. Anal., vol. 96, no. 9, pp. 1528–1546, 2017, doi: 10.1080/00036811.2016.1276175.
    7. J. Giesselmann and T. Pryer, “A posteriori analysis for dynamic model adaptation in convection  dominated problems,” Math. Models Methods Appl. Sci. (M3AS), vol. 27, no. 13, pp. 2381-- 2423, 2017, doi: 10.1142/S0218202517500476.
    8. J. Giesselmann, C. Lattanzio, and A. E. Tzavaras, “Relative Energy for the Korteweg Theory and Related Hamiltonian Flows in Gas Dynamics,” ARCHIVE FOR RATIONAL MECHANICS AND ANALYSIS, vol. 223, no. 3, pp. 1427–1484, 2017, doi: 10.1007/s00205-016-1063-2.
    9. D. Gläser, R. Helmig, B. Flemisch, and H. Class, “A discrete fracture model for two-phase flow in fractured porous media,” Advances in Water Resources, vol. 110, pp. 335--348, 2017, doi: 10.1016/j.advwatres.2017.10.031.
    10. G. Goebel and F. Allgöwer, “Semi-explicit MPC based on subspace clustering,” Automatica, vol. 83, pp. 309--316, 2017, doi: 10.1016/j.automatica.2017.06.036.
    11. G. Goebel and F. Allgöwer, “New results on semi-explicit and almost explicit MPC algorithms,” at-Automatisierungstechnik, vol. 65, pp. 245--259, 2017, doi: 10.1515/auto-2017-0006.
    12. M. Greis, H. Schuff, M. Kleiner, N. Henze, and A. Schmidt, Input Controls for Entering Uncertain Data: Probability Distribution Sliders. 2017.
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