A Learned Generalized Geodesic Distance Function-Based Approach for Node Feature Augmentation on Graphs-Reference-Cited by-同舟云学术

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A Learned Generalized Geodesic Distance Function-Based Approach for Node Feature Augmentation on Graphs

Published:2024-08-24 Issue: Volume: Page:49-58
ISSN:
Container-title:Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Azad Amitoz¹^ORCID,Fang Yuan¹^ORCID

Affiliation:

1. Singapore Management University, Singapore, Singapore

Funder

Ministry of Education, Singapore

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3637528.3671858

Reference38 articles.

1. Shortest-Path Kernels on Graphs

2. Benjamin Chamberlain, James Rowbottom, Davide Eynard, Francesco Di Giovanni, Xiaowen Dong, and Michael Bronstein. 2021. Beltrami Flow and Neural Diffusion on Graphs. Advances in Neural Information Processing Systems, Vol. 34 (2021).

3. Benjamin Paul Chamberlain, James Rowbottom, Maria Gorinova, Stefan Webb, Emanuele Rossi, and Michael M Bronstein. 2021. GRAND: Graph Neural Diffusion. In ICML.

4. Ricky TQ Chen Yulia Rubanova Jesse Bettencourt and David Duvenaud. 2018. Neural ordinary differential equations. In NeurIPS.

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