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 ...

for JavaScript (and TypeScript) programs that use the Node.js platform. The analyzer design is based on ideas from JAM [1], TAPIR [2] and ACG [3] with support for approximate interpretation [4] and ...