Dec 23, 2020 · A common objective of hyperbolic embedding is to maximize the likelihood function of the hyperbolic network model. The difficulty is that the ...

In this paper, we propose a hyperbolic embedding method for weighted networks based on a generative network model. We prove that hyperbolic embedding is a ...

This paper proposes a hyperbolic embedding method for weighted networks and shows that the proposed method achieves good embedding performance with respect ...

A common objective of hyperbolic embedding is to maximize the likelihood function of the hyperbolic network model. The difficulty is that the likelihood ...

A common objective of hyperbolic embedding is to maximize the likelihood function of the hyperbolic network model. The difficulty is that the likelihood ...

Oct 8, 2024 · We propose embedding into a weighted space, which is closely related to hyperbolic geometry but mathematically simpler.

To uncover the latent hyperbolic geometry of scale-free networks, hyperbolic embedding methods embed a network into a hyperbolic space. For instance ...

Dec 16, 2019 · We introduce Mercator, a reliable embedding method to map real complex networks into their hyperbolic latent geometry. The method assumes ...

We argue that embeddings into hyperbolic geometry can be used to monitor structural change in financial networks.

Find out what the research says about 'How do hyperbolic embeddings enhance the analysis of complex networks?'