Many complex systems can be modeled as irregular networks, with hubs and communities. Researcher Kay Martin Bogerd of the Department of Mathematics and Computer Science has investigated how existing community detection methods can be extended to a setting of inhomogeneous random graphs. The results offer new insights in the working of extremely large networks, such as the internet, social media or the brain. Bogerd defended his thesis on 17 February 2021.
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Detecting planted structures in random graphs
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