Lorentzian Logic: Visualizing High-Fidelity Graph Hierarchies in Hyperbolic Space

Table of Links

Related Work
Preliminaries and Notations
Differentiable Structural Information

4.1. A New Formulation

4.2. Properties

4.3. Differentiability & Deep Graph Clustering
LSEnet

5.1. Embedding Leaf Nodes

5.2. Learning Parent Nodes

5.3. Hyperbolic Partitioning Tree
Experiments

6.1. Graph Clustering

6.2. Discussion on Structural Entropy
Conclusion, Broader Impact, and References Appendix

The hyperbolic partitioning trees of Cora is visualized in Fig. 6, where different clusters are distinguished by colors.

Table 4. The notation descriptions.

Table 5. The statistics of the datasets.

Figure 6. Visualization of hyperbolic partitioning trees of Cora.

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Authors:

(1) Li Sun, North China Electric Power University, Beijing 102206, China (ccesunli@ncepu.edu);

(2) Zhenhao Huang, North China Electric Power University, Beijing 102206, China;

(3) Hao Peng, Beihang University, Beijing 100191, China;

(4) Yujie Wang, North China Electric Power University, Beijing 102206, China;

(5) Chunyang Liu, Didi Chuxing, Beijing, China;

(6) Philip S. Yu, University of Illinois at Chicago, IL, USA.

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This paper is available on arxiv under CC BY-NC-SA 4.0 Deed (Attribution-Noncommercial-Sharelike 4.0 International) license.

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