Related items
Showing items related by title, author, creator and subject.
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Graph-Theoretical Constructions for Graph Entropy and Network Coding Based Communications
Gadouleau, M; Riis, S (2011-10) -
Learning Backtrackless Aligned-Spatial Graph Convolutional Networks for Graph Classification.
Bai, L; Cui, L; Jiao, Y; Rossi, L; Hancock, E (2020-07-24)In this paper, we develop a novel Backtrackless Aligned-Spatial Graph Convolutional Network (BASGCN) model to learn effective features for graph classification. Our idea is to transform arbitrary-sized graphs into fixed-sized ... -
Visibility graphs for fMRI data: Multiplex temporal graphs and their modulations across resting-state networks.
Sannino, S; Stramaglia, S; Lacasa, L; Marinazzo, D (2017-10-01)Visibility algorithms are a family of methods that map time series into graphs, such that the tools of graph theory and network science can be used for the characterization of time series. This approach has proved a ...