6 citations · 8 across the 9 of their papers we have counts for
10 papers
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…
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…
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…
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…
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…
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…
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…
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…
Network Diffusion -- Framework to Simulate Spreading Processes in Complex Networks
Michał Czuba, Mateusz Nurek, Damian Serwata +5
With the advancement of computational network science, its research scope has significantly expanded beyond static graphs to encompass more complex structures. The introduction of…
Rank-Refining Seed Selection Methods for Budget Constrained Influence Maximisation in Multilayer Networks under Linear Threshold Model
Michał Czuba, Piotr Bródka
The problem of selecting an optimal seed set to maximise influence in networks has been a subject of intense research in recent years. However, despite numerous works addressing th…