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Augmentations of Forman's Ricci Curvature and their Applications in Community Detection
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The notion of curvature on graphs has recently gained traction in the networks community, with the Ollivier-Ricci curvature (ORC) in particular being used for several tasks in network analysis, such as community detection. In this work, we choose a different approach and study augmentations of the discretization of the Ricci curvature proposed by Forman (AFRC). We empirically and theoretically investigate its relation to the ORC and the un-augmented Forman-Ricci curvature. In particular, we provide evidence that the AFRC frequently gives sufficient insight into the structure of a network to be used for community detection, and therefore provides a computationally cheaper alternative to previous ORC-based methods. Our novel AFRC-based community detection algorithm is competitive with an ORC-based approach.
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Markov and lattice bases for Forman-Ricci curvature of graphs
Indispensable Markov moves for sampling graphs with fixed degree and Forman-Ricci curvature sequences have degree at least quadratic in the maximum degree, and degree-3 moves still span the lattice.
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