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hybrid-graph-benchmark

Authors: Zehui; Xiangyu; Mingzhu; Guy-Bart; , Pietro; Yiren;

hybrid-graph-benchmark

Abstract

This is a benchmark dataset for evaluating hybrid-graph (hypergraph and hierarchical graph) learning algorithms. It contains: 21 real-world higer-order graphs from the domains of biology, social media, and wikipedia For accessing additional functionalities, please access through Project Page Built-in functionalities for preprocessing hybrid-graphs A framework to easily train and evaluate Graph Neural Networks

Keywords

Machine Learning, Hypergraph, Graph Neural Networks, Hybrid-graph

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
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96