collaborators

9 papers

cs.LG2026

Graph Data Augmentation via Contrastive Generator Inversion ()

Mateusz Stolarski, Michał Czuba, Łukasz Kraiński +4

Graphs provide a natural representation of many complex systems, ranging from social platforms to ecosystems. However, the development of graph-based machine learning methods is of…

cs.SI2026

Graph Reduction in Multirelational Networks: A Spreading-Oriented Reduction Benchmark

Mateusz Stolarski, Michał 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…

cs.LG2026

Towards Graph Foundation Models for Dynamics in Complex Networked Systems: Lessons from Super-Spreader Identification in Multilayer Networks

Michał Czuba, 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…

cs.CE2026

The Elusive Nature of Roughness: Linking Hydraulics and Graph Theory for Water Distribution Networks Model Calibration

Karol Dykiert, Mateusz Stolarski, Michał 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…

cs.SI2026

Twinning Complex Networked Systems: Data-Driven Calibration of the mABCD Synthetic Graph Generator

Piotr Bródka, Michał Czuba, Bogumił Kamiński +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…

cs.SI2026

Beyond Individual Influence: The Role of Echo Chambers and Community Seeding in the Multilayer three state q-Voter Model

Igor Hołowacz, 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…

cs.SI2025

Multilayer Artificial Benchmark for Community Detection (mABCD)

Łukasz Kraiński, Michał 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…

cs.SI2025

Identifying Super Spreaders in Multilayer Networks

Michał Czuba, Mateusz Stolarski, Adam Piróg +2

Identifying super-spreaders can be framed as a subtask of the influence maximisation problem. It seeks to pinpoint agents within a network that, if selected as single diffusion see…

cs.SI2025

Applicability of the Minimal Dominating Set for Influence Maximization in Multilayer Networks

Michał Czuba, Mingshan Jia, Piotr Bródka +1

The minimal dominating set (MDS) is a well-established concept in network controllability and has been successfully applied in various domains, including sensor placement, network…