| Guidelines for experimental algorithmics: A case study in network analysis E Angriman, A van der Grinten, M von Looz, H Meyerhenke, M Nöllenburg, ... Algorithms 12 (7), 127, 2019 | 27 | 2019 |
| Group Centrality Maximization for Large-scale Graphs E Angriman, A van der Grinten, A Bojchevski, D Zügner, S Günnemann, ... 2020 Proceedings of the Twenty-Second Workshop on Algorithm Engineering and …, 2020 | 20 | 2020 |
| Scaling up network centrality computations–A brief overview A van der Grinten, E Angriman, H Meyerhenke it-Information Technology, 0 | 16 | |
| Scalable Katz Ranking Computation in Large Static and Dynamic Graphs A van der Grinten, E Bergamini, O Green, DA Bader, H Meyerhenke 26th Annual European Symposium on Algorithms (ESA 2018) 112, 42:1 - 42:14, 2018 | 14 | 2018 |
| pfolioUZK: Solver description A Wotzlaw, A van der Grinten, E Speckenmeyer, S Porschen Proceedings of SAT Challenge, 45, 2012 | 14 | 2012 |
| Approximation of the Diagonal of a Laplacian's Pseudoinverse for Complex Network Analysis E Angriman, M Predari, A van der Grinten, H Meyerhenke arXiv preprint arXiv:2006.13679, 2020 | 12 | 2020 |
| Group-Harmonic and Group-Closeness Maximization–Approximation and Engineering∗ E Angriman, R Becker, G D'Angelo, H Gilbert, A van der Grinten, ... 2021 Proceedings of the Workshop on Algorithm Engineering and Experiments …, 2021 | 11 | 2021 |
| Effectiveness of pre-and inprocessing for CDCL-based SAT solving A Wotzlaw, A van der Grinten, E Speckenmeyer arXiv preprint arXiv:1310.4756, 2013 | 11 | 2013 |
| Scaling betweenness approximation to billions of edges by MPI-based adaptive sampling A van der Grinten, H Meyerhenke 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS …, 2020 | 10 | 2020 |
| High-Quality Hierarchical Process Mapping MF Faraj, A van der Grinten, H Meyerhenke, JL Träff, C Schulz arXiv preprint arXiv:2001.07134, 2020 | 10 | 2020 |
| New Approximation Algorithms for Forest Closeness Centrality–for Individual Vertices and Vertex Groups A van der Grinten, E Angriman, M Predari, H Meyerhenke Proceedings of the 2021 SIAM International Conference on Data Mining (SDM …, 2021 | 9 | 2021 |
| Local search for group closeness maximization on big graphs E Angriman, A van der Grinten, H Meyerhenke 2019 IEEE International Conference on Big Data (Big Data), 711-720, 2019 | 9 | 2019 |
| satUZK: Solver description A van der Grinten, A Wotzlaw, E Speckenmeyer, S Porschen Proceedings of SAT Competition 2013, 82, 2013 | 7 | 2013 |
| SAT-and-Reduce for Vertex Cover: Accelerating Branch-and-Reduce by SAT Solving R Plachetta, A van der Grinten 2021 Proceedings of the Workshop on Algorithm Engineering and Experiments …, 2021 | 6 | 2021 |
| Algorithms for large-scale network analysis and the networkit toolkit E Angriman, A van der Grinten, M Hamann, H Meyerhenke, M Penschuck Algorithms for Big Data: DFG Priority Program 1736, 3-20, 2023 | 5 | 2023 |
| Scaling up Network Centrality Computations * A van der Grinten, H Meyerhenke 2019 Design, Automation & Test in Europe Conference & Exhibition (DATE …, 2019 | 2 | 2019 |
| An MPI-Parallel Algorithm for Static and Dynamic Top-k Harmonic Centrality A van der Grinten, G Custers, D Le Thanh, H Meyerhenke 2022 IEEE 34th International Symposium on Computer Architecture and High …, 2022 | 1 | 2022 |
| Interactive Visualization of Protein RINs using NetworKit in the Cloud E Angriman, F Brandt-Tumescheit, L Franke, A van der Grinten, ... 2022 IEEE International Parallel and Distributed Processing Symposium …, 2022 | 1 | 2022 |
| A Fast Data Structure for Dynamic Graphs Based on Hash-Indexed Adjacency Blocks A van der Grinten, M Predari, F Willich 20th International Symposium on Experimental Algorithms (SEA 2022), 2022 | 1 | 2022 |
| satUZK-seq and satUZK-ddc: Solver description A van der Grinten SAT COMPETITION 2017, 30, 2017 | 1 | 2017 |
