Computationally Tractable Riemannian Manifolds for Graph Embeddings

1 code implementation • 20 Feb 2020 • Calin Cruceru, Gary Bécigneul, Octavian-Eugen Ganea

Representing graphs as sets of node embeddings in certain curved Riemannian manifolds has recently gained momentum in machine learning due to their desirable geometric inductive biases, e. g., hierarchical structures benefit from hyperbolic geometry.

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