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 ...

America’s overdose crisis isn’t the simple story we’ve been told for years. A new investigation reveals how two key graphs — one famous, one ignored — shift entirely the way we understand what ...