Random Walks on Multiplex Networks
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Abstract (arXiv)
Multiplex networks are receiving increasing interests because they allow to model relationships between networked agents on several layers simultaneously. In this supplementary material for the paper "Navigability of interconnected networks under random failures", we extend well-known random walks to multiplexes and we introduce a new type of walk that can exist only in multiplexes. We derive exact expressions for vertex occupation time and the coverage. Finally, we show how the efficiency in exploring the multiplex critically depends on the underlying topology of layers, the weight of their inter-connections and the strategy adopted to walk.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 3 Jun 2013.
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Citing papers per year: 2021: 6; 2022: 2; 2023: 2.
10 papers.
- 2021mGNN: Generalizing the Graph Neural Networks to the Multilayer Casecited by 4
- 2021Explainable, automated urban interventions to improve pedestrian and vehicle safetycited by 3
- 2021Universal Multilayer Network Exploration by Random Walk with Restartcited by 2
- 2023Zoo Guide to Network Embeddingcited by 2
- 2021Survey of Generative Methods for Social Media Analysiscited by 1
- 2022Systematic assessment of the quality of fit of the stochastic block model for empirical networkscited by 1
- 2021A Tensor-Based Formulation of Hetero-functional Graph Theorycited by 0
- 2021Thematic recommendations on knowledge graphs using multilayer networkscited by 0
- 2022Reconstructing Sparse Multiplex Networks with Application to Covert Networkscited by 0
- 2023Learning the Right Layers: a Data-Driven Layer-Aggregation Strategy for Semi-Supervised Learning on Multilayer Graphscited by 0
- 2023Learning the Right Layers: a Data-Driven Layer-Aggregation Strategy for Semi-Supervised Learning on Multilayer Graphs31 May 2023
- 2023Zoo Guide to Network Embedding5 May 2023
- 2022Reconstructing Sparse Multiplex Networks with Application to Covert Networks29 Jul 2022
- 2022Systematic assessment of the quality of fit of the stochastic block model for empirical networks5 Jan 2022
- 2021Survey of Generative Methods for Social Media Analysis13 Dec 2021
- 2021Explainable, automated urban interventions to improve pedestrian and vehicle safety22 Oct 2021
- 2021mGNN: Generalizing the Graph Neural Networks to the Multilayer Case21 Sep 2021
- 2021Universal Multilayer Network Exploration by Random Walk with Restart9 Jul 2021
- 2021Thematic recommendations on knowledge graphs using multilayer networks12 May 2021
- 2021A Tensor-Based Formulation of Hetero-functional Graph Theory14 Jan 2021