Anton Tsitsulin

SGR: Self-Supervised Spectral Graph Representation Learning

2018 · arXiv (Cornell University)

Representing a graph as a vector is a challenging task; ideally, the representation should be easily computable and conducive to efficient comparisons among graphs, tailored to the particular data and analytical task at hand. Unfortunately, …

UGSL: A Unified Framework for Benchmarking Graph Structure Learning

2023 · arXiv (Cornell University)

Graph neural networks (GNNs) demonstrate outstanding performance in a broad range of applications. While the majority of GNN applications assume that a graph structure is given, some recent methods substantially expanded the applicability of GNNs …