One of the fundamental problems in network analysis is detecting community structure in
multi-layer networks, of which each layer represents one type of edge information among the …

Network thinking and network analysis are rapidly expanding features of ecological
research. Network analysis of ecological systems include representations and modelling of …

Graph clustering aims at discovering a natural grouping of the nodes such that similar nodes
are assigned to a common cluster. Many different algorithms have been proposed in the …

The fundamental goal of self-supervised learning (SSL) is to produce useful representations
of data without access to any labels for classifying the data. Modern methods in SSL, which …

During the past several years, multi-layer network community detection has drawn an
increasing amount of attention and many approaches have been developed from different …

While frequency-domain algorithms have been demonstrated to be powerful for
conventional nonlinear signal processing, there is still not much progress in literature …

We investigate the problem of community detection in multidimensional networks, that is,
networks where entities engage in various interaction types (dimensions) simultaneously …

The identification of important nodes (vertexes) in multilayer networks has aroused many
scholars' attention and various centrality methods have deen developed. However, the …

Community detection in multiview networks has drawn an increasing amount of attention in
recent years. Many approaches have been developed from different perspectives. Despite …

Community detection in real-world graphs has been shown to benefit from using multi-
aspect information, eg, in the form of “means of communication” between nodes in the …