Hasso-Plattner-Institut
Prof. Dr. Tobias Friedrich
 

Publications of Marcus Pappik

The following listing contains all publications of Marcus Pappik. Further publications of the research group can be found on the current list of publications and the complete list of publications. Individual listings are available externally on DBLP and Google Scholar or locally as PDF.

[ 2024 ] [ 2023 ] [ 2022 ] [ 2021 ] [ 2019 ] [ 2018 ] [ 2017 ]

2024 [ nach oben ]

  • Analysis of the survival ... - Download
    Friedrich, Tobias; Göbel, Andres; Klodt, Nicolas; Krejca, Martin S.; Pappik, Marcus Analysis of the survival time of the SIRS process via expansionElectronic Journal of Probability 2024: 1–29
     
  • The Irrelevance of Influe... - Download
    Friedrich, Tobias; Göbel, Andreas; Klodt, Nicolas; Krejca, Martin S.; Pappik, Marcus The Irrelevance of Influencers: Information Diffusion with Re-Activation and Immunity Lasts Exponentially Long on Social Network ModelsAnnual AAAI Conference on Artificial Intelligence 2024
     
  • From Market Saturation to... - Download
    Friedrich, Tobias; Göbel, Andreas; Klodt, Nicolas; Krejca, Martin S.; Pappik, Marcus From Market Saturation to Social Reinforcement: Understanding the Impact of Non-Linearity in Information Diffusion ModelsThe 23rd International Conference on Autonomous Agents and Multi-Agent Systems 2024
     

2023 [ nach oben ]

  • Polymer Dynamics via Cliq... - Download
    Friedrich, Tobias; Göbel, Andreas; Krejca, Martin S.; Pappik, Marcus Polymer Dynamics via Cliques: New Conditions for ApproximationsTheoretical Computer Science 2023: 230–252
     
  • Fixed Parameter Multi-Obj... - Download
    Baguley, Samuel; Friedrich, Tobias; Neumann, Aneta; Neumann, Frank; Pappik, Marcus; Zeif, Ziena Fixed Parameter Multi-Objective Evolutionary Algorithms for the W-Separator ProblemGenetic and Evolutionary Computation Conference (GECCO) 2023
     
  • Perfect Sampling for Hard... - Download
    Anand, Konrad; Göbel, Andreas; Pappik, Marcus; Perkins, Will Perfect Sampling for Hard Spheres from Strong Spatial MixingInternational Conference on Randomization and Computation (Random) 2023: 38:1–38:18
     

2022 [ nach oben ]

  • A Spectral Independence V... - Download
    Friedrich, Tobias; Göbel, Andreas; Krejca, Martin S.; Pappik, Marcus A Spectral Independence View on Hard Spheres via Block DynamicsSIAM Journal on Discrete Mathematics 2022: 2282–2322
     
  • Algorithms for hard-const... - Download
    Friedrich, Tobias; Göbel, Andreas; Katzmann, Maximilian; Krejca, Martin S.; Pappik, Marcus Algorithms for hard-constraint point processes via discretizationInternational Computing and Combinatorics Conference (COCOON) 2022: 242–254
     
  • Analysis of a Gray-Box Op... - Download
    Baguley, Samuel; Friedrich, Tobias; Timo, Kötzing; Li, Xiaoyue; Pappik, Marcus; Zeif, Ziena Analysis of a Gray-Box Operator for Vertex CoverGenetic and Evolutionary Computation Conference (GECCO) 2022: 1363–1371
     

2021 [ nach oben ]

  • A spectral independence v... - Download
    Friedrich, Tobias; Göbel, Andreas; Krejca, Martin S.; Pappik, Marcus A spectral independence view on hard spheres via block dynamicsInternational Colloquium on Automata, Languages and Programming (ICALP) 2021: 66:1–66:15
     

2019 [ nach oben ]

  • Convergence and Hardness ... - Download
    Echzell, Hagen; Friedrich, Tobias; Lenzner, Pascal; Molitor, Louise; Pappik, Marcus; Schöne, Friedrich; Sommer, Fabian; Stangl, David Convergence and Hardness of Strategic Schelling SegregationWeb and Internet Economics (WINE) 2019: 156–170
     

2018 [ nach oben ]

  • Kumar Shekar, Arvind; Pappik, Marcus; Iglesias Sánchez, Patricia; Müller, Emmanuel Selection of Relevant and Non-Redundant Multivariate Ordinal Patterns for Time Series ClassificationDiscovery Science (DS) 2018: 224–240
     

2017 [ nach oben ]

  • Framework for Exploring a... - Download
    Kirsch, Louis; Riekenbrauck, Niklas; Thevessen, Daniel; Pappik, Marcus; Stebner, Axel; Kunze, Julius; Meissner, Alexander; Kumar Shekar, Arvind; Müller, Emmanuel Framework for Exploring and Understanding Multivariate CorrelationsMachine Learning and Knowledge Discovery in Databases (ECML/PKDD) 2017: 404–408