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KNN Lifting (Graph to Hypergraph)
Guillermo Bernárdez edited this page Mar 6, 2025
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For each node in the graph, the method finds the k nearest nodes by using the Euclidean distance between the vectors of features. The set of k nodes found is considered as an hyperedge. The proces is repeated for all nodes in the graph.
Reference: Hypergraph Learning: Methods and Practices
- Defining GCCNs
- Defining backbone models
- Reproducing experiments
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Graph to Simplicial Complex
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Graph to Cell Complex
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Graph to Hypergraph
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Graph to Combinatorial
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Pointcloud to Graph
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Pointcloud to Simplicial
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Pointcloud to Hypergraph
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Hypergraph to Simplicial
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Hypergraph to Combinatorial