A hypergraph neural network using symmetric simplicial sets and a degree-zero sheaf Laplacian is tested on node classification benchmarks, with a graph-reduction theorem that has a gap.
Hypergraph learning: Methods and practices,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2025 1verdicts
REJECT 1representative citing papers
citing papers explorer
-
Hypergraph Neural Sheaf Diffusion: A Symmetric Simplicial Set Framework for Higher-Order Learning
A hypergraph neural network using symmetric simplicial sets and a degree-zero sheaf Laplacian is tested on node classification benchmarks, with a graph-reduction theorem that has a gap.