53 citations · 113 across the 4 of their papers we have counts for
4 papers
Power to the Relational Inductive Bias: Graph Neural Networks in Electrical Power Grids
Martin Ringsquandl, Houssem Sellami, Marcel Hildebrandt +4
The application of graph neural networks (GNNs) to the domain of electrical power grids has high potential impact on smart grid monitoring. Even though there is a natural correspon…
Generating random networks with given degree-degree correlations and degree-dependent clustering
Andreas Pusch, Sebastian Weber, Markus Porto
Random networks are widely used to model complex networks and research their properties. In order to get a good approximation of complex networks encountered in various disciplines…
Generation of arbitrarily two-point correlated random networks
Sebastian Weber, Markus Porto
Random networks are intensively used as null models to investigate properties of complex networks. We describe an efficient and accurate algorithm to generate arbitrarily two-point…
Multicomponent reaction-diffusion processes on complex networks
Sebastian Weber, Markus Porto
We study the reaction-diffusion process on uncorrelated scale-free networks analytically. By a mean-field ansatz we derive analytical expressions for the part…