8 papers
Graph Reduction in Multirelational Networks: A Spreading-Oriented Reduction Benchmark
Mateusz Stolarski, MichaÅ Czuba, Piotr Bielak +1
Real-world networks are inherently incomplete, noisy, and dynamically evolving, making it difficult to capture all actors and their relationships. Their scale often renders direct…
Towards Graph Foundation Models for Dynamics in Complex Networked Systems: Lessons from Super-Spreader Identification in Multilayer Networks
MichaŠCzuba, Mateusz Stolarski, Adam Piróg +2
Network dynamics - including spreading, influence maximisation, and epidemic modelling - remain largely confined to the transductive paradigm, where models are trained on a single…
The Elusive Nature of Roughness: Linking Hydraulics and Graph Theory for Water Distribution Networks Model Calibration
Karol Dykiert, Mateusz Stolarski, MichaÅ Czuba +2
Accurate pipe roughness estimation in large-scale water distribution networks is often hindered by the high cost of traditional field methods. This study investigates whether netwo…
Twinning Complex Networked Systems: Data-Driven Calibration of the mABCD Synthetic Graph Generator
Piotr Bródka, MichaÅ Czuba, BogumiÅ KamiÅski +4
The increasing availability of relational data has contributed to a growing reliance on network-based representations of complex systems. Over time, these models have evolved to ca…
Beyond Individual Influence: The Role of Echo Chambers and Community Seeding in the Multilayer three state q-Voter Model
Igor HoÅowacz, Piotr Bródka
The diffusion of complex opinions is severely hindered in multilayer social networks by echo chambers and cognitive consistency mechanisms. We investigate Influence Maximization st…
Multilayer Artificial Benchmark for Community Detection (mABCD)
Åukasz KraiÅski, MichaÅ Czuba, Piotr Bródka +3
One of the most persistent challenges in network science is the development of various synthetic graph models to support subsequent analyses. Among the most notable frameworks addr…