VERSE
VERtex Similarity Embeddings
VERtex Similarity Embeddings (VERSE) is a simple, versatile, and memory-efficient method that derives graph embeddings explicitly calibrated to preserve the distributions of a selected vertex-to-vertex similarity measure. VERSE learns such embeddings by training a single-layer neural network.

Source: [Tsitsulin et al.](https://arxiv.org/pdf/1803.04742v1.pdf)

Image source: [Tsitsulin et al.](https://arxiv.org/pdf/1803.04742v1.pdf)
VERSE: Versatile Graph Embeddings from Similarity Measures
https://paperswithcode.com/paper/verse-versatile-graph-embeddings-from
VERSE: Versatile Graph Embeddings from Similarity Measures