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Southern, J.* ; Wayland, J.D. ; Bronstein, M.D.* ; Rieck, B.

Curvature Filtrations for Graph Generative Model Evaluation.

In: (37th Conference on Neural Information Processing Systems (NeurIPS), 10-16 December 2023, New Orleans, LA). 10010 North Torrey Pines Rd, La Jolla, California 92037 Usa: Neural Information Processing Systems (nips), 2023. 26
Graph generative model evaluation necessitates understanding differences between graphs on the distributional level. This entails being able to harness salient attributes of graphs in an efficient manner. Curvature constitutes one such property that has recently proved its utility in characterising graphs. Its expressive properties, stability, and practical utility in model evaluation remain largely unexplored, however. We combine graph curvature descriptors with emerging methods from topological data analysis to obtain robust, expressive descriptors for evaluating graph generative models.
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Publication type Article: Conference contribution
Corresponding Author
Keywords Ricci Curvature
ISSN (print) / ISBN 1049-5258
Conference Title 37th Conference on Neural Information Processing Systems (NeurIPS)
Conference Date 10-16 December 2023
Conference Location New Orleans, LA
Quellenangaben Volume: , Issue: , Pages: 26 Article Number: , Supplement: ,
Publisher Neural Information Processing Systems (nips)
Publishing Place 10010 North Torrey Pines Rd, La Jolla, California 92037 Usa
Non-patent literature Publications
Institute(s) Institute of AI for Health (AIH)
Grants Hightech Agenda Bavaria
Bavarian State Government
EPSRC Turing AI World-Leading Researcher Fellowship