Generating Massive Scale-Free Networks under Resource Constraints. - Ulrich Meyer 001; Manuel Penschuck (ALENEX, 2016)

I/O-efficient Generation of Massive Graphs Following the LFR Benchmark. - Michael Hamann; Ulrich Meyer 001; Manuel Penschuck; Dorothea Wagner (ALENEX, 2017)

Generating Practical Random Hyperbolic Graphs in Near-Linear Time and with Sub-Linear Memory. - Manuel Penschuck (SEA, 2017)

Large-scale Graph Generation and Big Data: An Overview on Recent Results. - Ulrich Meyer 001; Manuel Penschuck (Bull. EATCS, 2017)

Parallel and I/O-efficient Randomisation of Massive Networks using Global Curveball Trades. - Corrie Jacobien Carstens; Michael Hamann; Ulrich Meyer 001; Manuel Penschuck; Hung Tran; Dorothea Wagner (ESA, 2018)

I/O-Efficient Generation of Massive Graphs Following the LFR Benchmark. - Michael Hamann; Ulrich Meyer 001; Manuel Penschuck; Hung Tran; Dorothea Wagner (ACM J. Exp. Algorithmics, 2018)

Fragile Complexity of Comparison-Based Algorithms. - Peyman Afshani; Rolf Fagerberg; David Hammer; Riko Jacob; Irina Kostitsyna; Ulrich Meyer 001; Manuel Penschuck; Nodari Sitchinava (ESA, 2019)

Bidirectional Text Compression in External Memory. - Patrick Dinklage; Jonas Ellert; Johannes Fischer 001; Dominik Köppl; Manuel Penschuck (ESA, 2019)

Communication-free massively distributed graph generation. - Daniel Funke; Sebastian Lamm; Ulrich Meyer 001; Manuel Penschuck; Peter Sanders 001; Christian Schulz 003; Darren Strash; Moritz von Looz (J. Parallel Distributed Comput., 2019)

Simulating Population Protocols in Sub-Constant Time per Interaction. - Petra Berenbrink; David Hammer; Dominik Kaaser; Ulrich Meyer 001; Manuel Penschuck; Hung Tran (ESA, 2020)

The random 2-SAT partition function. - Dimitris Achlioptas; Amin Coja-Oghlan; Max Hahn-Klimroth; Joon Lee; Noëla Müller; Manuel Penschuck; Guangyan Zhou (CoRR, 2020)

Recent Advances in Scalable Network Generation. - Manuel Penschuck; Ulrik Brandes; Michael Hamann; Sebastian Lamm; Ulrich Meyer 001; Ilya Safro; Peter Sanders 001; Christian Schulz 003 (CoRR, 2020)

Optimal group testing under real world restrictions. - Oliver Gebhard; Max Hahn-Klimroth; Olaf Parczyk; Manuel Penschuck; Maurice Rolvien (CoRR, 2020)

Large-scale graph generation: Recent results of the SPP 1736 - Part II. - Ulrich Meyer 001; Manuel Penschuck (it Inf. Technol., 2020)

An Experimental Study of External Memory Algorithms for Connected Components. - Gerth Stølting Brodal; Rolf Fagerberg; David Hammer; Ulrich Meyer 001; Manuel Penschuck; Hung Tran (SEA, 2021)

The number of satisfying assignments of random 2-SAT formulas. - Dimitris Achlioptas; Amin Coja-Oghlan; Max Hahn-Klimroth; Joon Lee; Noëla Müller; Manuel Penschuck; Guangyan Zhou (Random Struct. Algorithms, 2021)

Scalable generation of random graphs - Manuel Penschuck (2021)

Recent Advances in Scalable Network Generation1. - Manuel Penschuck; Ulrik Brandes; Michael Hamann; Sebastian Lamm; Ulrich Meyer 001; Ilya Safro; Peter Sanders 001; Christian Schulz 003 (Massive Graph Analytics, 2022)

Generating Synthetic Graph Data from Random Network Models. - Ulrich Meyer 001; Manuel Penschuck (Algorithms for Big Data, 2022)

Algorithms for Large-Scale Network Analysis and the NetworKit Toolkit. - Eugenio Angriman; Alexander van der Grinten; Michael Hamann; Henning Meyerhenke; Manuel Penschuck (Algorithms for Big Data, 2022)

Engineering Uniform Sampling of Graphs with a Prescribed Power-law Degree Sequence. - Daniel Allendorf; Ulrich Meyer 001; Manuel Penschuck; Hung Tran; Nick Wormald (ALENEX, 2022)

Efficient and Accurate Group Testing via Belief Propagation: An Empirical Study. - Amin Coja-Oghlan; Max Hahn-Klimroth; Philipp Loick; Manuel Penschuck (SEA, 2022)

Algorithms for Large-scale Network Analysis and the NetworKit Toolkit. - Eugenio Angriman; Alexander van der Grinten; Michael Hamann; Henning Meyerhenke; Manuel Penschuck (CoRR, 2022)

Near-Optimal Sparsity-Constrained Group Testing: Improved Bounds and Algorithms. - Oliver Gebhard; Max Hahn-Klimroth; Olaf Parczyk; Manuel Penschuck; Maurice Rolvien; Jonathan Scarlett; Nelvin Tan (IEEE Trans. Inf. Theory, 2022)

Efficiently generating geometric inhomogeneous and hyperbolic random graphs. - Thomas Bläsius; Tobias Friedrich 001; Maximilian Katzmann; Ulrich Meyer 001; Manuel Penschuck; Christopher Weyand (Netw. Sci., 2022)

Parallel and I/O-Efficient Algorithms for Non-Linear Preferential Attachment. - Daniel Allendorf; Ulrich Meyer 001; Manuel Penschuck; Hung Tran (ALENEX, 2023)

PACE Solver Description: Exact (GUTHMI) and Heuristic (GUTHM). - Alexander Leonhardt; Holger Dell; Anselm Haak; Frank Kammer; Johannes Meintrup; Ulrich Meyer 001; Manuel Penschuck (IPEC, 2023)

Engineering Shared-Memory Parallel Shuffling to Generate Random Permutations In-Place. - Manuel Penschuck (SEA, 2023)

Parallel global edge switching for the uniform sampling of simple graphs with prescribed degrees. - Daniel Allendorf; Ulrich Meyer 001; Manuel Penschuck; Hung Tran (J. Parallel Distributed Comput., 2023)

Insights into (k, ρ)-Shortcutting Algorithms. - Alexander Leonhardt; Ulrich Meyer 001; Manuel Penschuck (ESA, 2024)

Uniform Sampling of Negative Edge Weights in Shortest Path Networks. - Lukas Geis; Daniel Allendorf; Thomas Bläsius; Alexander Leonhardt; Ulrich Meyer 001; Manuel Penschuck; Hung Tran (CoRR, 2024)

K-Rho-Shortcutting Heuristics. - Alexander Leonhardt; Ulrich Meyer 001; Manuel Penschuck (DROPS Artifacts, 2024)

Simpler, Better, Faster, Stronger: Revisiting a Successful Reduction Rule for Dominating Set. - Lukas Geis; Alexander Leonhardt; Johannes Meintrup; Ulrich Meyer 001; Manuel Penschuck (CoRR, 2025)