A Self-supervised Riemannian GNN with Time Varying Curvature for Temporal Graph Learning. (arXiv:2208.14073v1 [cs.LG])

Representation learning on temporal graphs has drawn considerable research
attention owing to its fundamental importance in a wide spectrum of real-world
applications. Though a number of studies succeed in obtaining time-dependent
representations, it still faces significant challenges. On the one hand, most
of the existing methods restrict the embedding space with a certain curvature.
However, the underlying geometry in fact shifts among the positive curvature
hyperspherical, zero curvature Euclidean and negative curvature hyperbolic
spaces in the evolvement over time. On …

arxiv graph graph learning learning temporal time