An explosion of user-generated data from online social networks motivates analysis to extract deep insights from this data’s graph at scale, even of social, temporal, spatial, and topical connections.
Abstract: This paper proposes a graph linear canonical transform (GLCT) by decomposing the linear canonical parameter matrix into fractional Fourier transform, scale transform, and chirp modulation ...
Abstract: Graph representation learning (GRL) has become a new learning paradigm, supporting a wide range of tasks such as node classification, link prediction, and graph classification. However, the ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback